diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..3216685 --- /dev/null +++ b/.env.example @@ -0,0 +1,8 @@ +GESTURAI_GESTURE_ACTION_MAP_PATH = 'gesture_map.json' +GESTURAI_DEFAULT_GESTURE_ACTION_MAP_PATH = 'default_gesture_map.json' +GESTURAI_GESTURE_INDEX_MAP_PATH = 'gesture_index_map.json' +GESTURAI_DEFAULT_GESTURE_INDEX_MAP_PATH = 'default_gesture_index_map.json' +GESTURAI_GESTURE_DATA_PATH = 'gesture_data/' +GESTURAI_DEFAULT_GESTURE_DATA_PATH = 'gesture_data/default/' +GESTURAI_GESTURE_MODEL_PATH = 'models/gesture_model.pth' +GESTURAI_DEFAULT_GESTURE_MODEL_PATH = 'models/gesture_model_default.pth' \ No newline at end of file diff --git a/.gitignore b/.gitignore index 02014fc..374c7db 100644 --- a/.gitignore +++ b/.gitignore @@ -2,4 +2,5 @@ gesture_data.pkl gesture_model.pth label_map.pkl __pycache__/ -venv/ \ No newline at end of file +venv/ +.env diff --git a/README.md b/README.md index fdeafe2..4f3fb57 100644 --- a/README.md +++ b/README.md @@ -7,14 +7,15 @@ A real-time hand gesture recognition system using MediaPipe and PyTorch to contr ## šŸ”§ Features - āœ… Real-time gesture recognition using webcam -- āœ… Context-aware gesture modes (`media_mode`, `word_mode`, `presentation_mode`) +- āœ… Context-specific gesture modes šŸ§  (`media_mode`, `word_mode`, `presentation_mode`) - switch between modes using gestures! - āœ… Customizable gesture-to-action mappings -- āœ… Streamlit UI for editing gesture mappings +- āœ… Create your own gestures! +- āœ… Streamlit UI for editing gestures and mappings - āœ… Cross-platform (macOS, Linux, Windows) --- -## šŸ“‚ Project Structure + --- ## šŸš€ Getting Started -### 1. Install Dependencies +### 1. šŸ§° Install Dependencies ```bash pip install -r requirements.txt ``` -### 2. Collect Gesture Data - -```bash -python collect_data.py -``` +--- -### 3. Train the Model +### 2. āš™ļø Customize Your Gestures and Map Gestures to Actions ```bash -python training.py +python -m streamlit run config.py ``` -### 4. Map Gestures to Actions +Use the configuration app to: +- Add, rename, relearn, or delete gestures: the app will walk you through the process of collecting data for the new gesture and automatically retrains the gesture recognition model! +- Change the way gestures trigger system actions or context changes: add or remove mappings, and add, remove, or rename contexts! -```bash -# Option A: Streamlit UI -streamlit run gesture_ui_mapper.py - -# Option B: CLI -python gesture_cli_mapper.py -``` +--- -### 5. Run Gesture Controller +### 3. šŸ” Run Gesture Controller ```bash -python run_gesture_control.py +python gesturai.py ``` --- @@ -89,32 +82,9 @@ python run_gesture_control.py --- -## šŸ§  Context Modes - -- `default` -- `word_mode` -- `media_mode` -- `presentation_mode` - -You can switch between modes using trigger gestures like `three_fingers`, `peace_sign`, or `ok_sign`. - ---- - -## šŸ” Customize Your Mappings - -Use `gesture_ui_mapper.py` to: - -- Add new gestures -- Map gestures to system actions -- Delete or reset mappings -- Save to `gesture_config.json` - ---- - ## šŸ“Œ Future Ideas -- Record your own custom gestures -- Add voice feedback or sound effects -- Integrate with specific apps (Zoom, PowerPoint, etc.) +- Extend to take voice commands +- Add sound effects or feedback +- Integrate with popular apps (Zoom, PowerPoint, etc.) - Cloud-hosted UI for remote gesture mapping - diff --git a/actions.py b/actions.py deleted file mode 100644 index 73d78b0..0000000 --- a/actions.py +++ /dev/null @@ -1,265 +0,0 @@ -import os -import webbrowser -import platform -import subprocess -from datetime import datetime -import time - -OS = platform.system() - -# -------------------------------------------- -# System Control Functions -# -------------------------------------------- - -def open_terminal(): - """Opens the terminal window based on OS.""" - try: - if OS == "Darwin": - os.system("open -a Terminal") # macOS - elif OS == "Linux": - os.system("gnome-terminal") # Linux (change if needed) - elif OS == "Windows": - os.system("start cmd") - except Exception as e: - print(f"Error opening terminal: {e}") - -def open_browser(): - """Opens the default web browser.""" - try: - webbrowser.open("https://www.google.com") - except Exception as e: - print(f"Error opening browser: {e}") - -def increase_volume(): - """Increases system volume based on OS.""" - try: - if OS == "Darwin": - os.system("osascript -e 'set volume output volume (output volume of (get volume settings) + 10)'") - elif OS == "Linux": - os.system("pactl set-sink-volume @DEFAULT_SINK@ +10%") - except Exception as e: - print(f"Error increasing volume: {e}") - -def decrease_volume(): - """Decreases system volume based on OS.""" - try: - if OS == "Darwin": - os.system("osascript -e 'set volume output volume (output volume of (get volume settings) - 10)'") - elif OS == "Linux": - os.system("pactl set-sink-volume @DEFAULT_SINK@ -10%") - except Exception as e: - print(f"Error decreasing volume: {e}") - -def take_screenshot(): - """Takes a screenshot with timestamped filename.""" - filename = f"screenshot_{datetime.now().strftime('%Y%m%d_%H%M%S')}.png" - try: - if OS == "Darwin": - os.system(f"screencapture {filename}") - elif OS == "Linux": - os.system(f"gnome-screenshot -f {filename}") - elif OS == "Windows": - os.system(f"nircmd.exe savescreenshot {filename}") # Requires nircmd.exe in PATH - except Exception as e: - print(f"Error taking screenshot: {e}") - -def lock_computer(): - """Locks the computer.""" - try: - if OS == "Windows": - os.system("rundll32.exe user32.dll,LockWorkStation") - elif OS == "Darwin": - os.system("/System/Library/CoreServices/Menu\\ Extras/User.menu/Contents/Resources/CGSession -suspend") - except Exception as e: - print(f"Error locking computer: {e}") - -def open_file_explorer(): - """Opens the file explorer.""" - try: - if OS == "Windows": - os.system("explorer") - elif OS == "Darwin": - os.system("open .") - except Exception as e: - print(f"Error opening file explorer: {e}") - -def minimize_all_windows(): - """Minimizes all windows.""" - _send_keyboard_shortcut(["win", "d"] if OS == "Windows" else ["fn", "f11"]) - -# -------------------------------------------- -# Clipboard & Editing Functions -# -------------------------------------------- - -def copy(): - _send_keyboard_shortcut(["ctrl", "c"] if OS == "Windows" else ["cmd", "c"]) - -def paste(): - _send_keyboard_shortcut(["ctrl", "v"] if OS == "Windows" else ["cmd", "v"]) - -def cut(): - _send_keyboard_shortcut(["ctrl", "x"] if OS == "Windows" else ["cmd", "x"]) - -def undo(): - _send_keyboard_shortcut(["ctrl", "z"] if OS == "Windows" else ["cmd", "z"]) - -def redo(): - _send_keyboard_shortcut(["ctrl", "y"] if OS == "Windows" else ["cmd", "shift", "z"]) - -def select_all(): - _send_keyboard_shortcut(["ctrl", "a"] if OS == "Windows" else ["cmd", "a"]) - -def save(): - _send_keyboard_shortcut(["ctrl", "s"] if OS == "Windows" else ["cmd", "s"]) - -def print_file(): - _send_keyboard_shortcut(["ctrl", "p"] if OS == "Windows" else ["cmd", "p"]) - -def find(): - _send_keyboard_shortcut(["ctrl", "f"] if OS == "Windows" else ["cmd", "f"]) - -# -------------------------------------------- -# Helper Function for Simulating Keypresses -# -------------------------------------------- - -def _send_keyboard_shortcut(keys): - try: - import pyautogui - - # macOS fix: replace 'cmd' with 'command' for pyautogui - fixed_keys = ['command' if k == 'cmd' else k for k in keys] - pyautogui.hotkey(*fixed_keys) - - except ImportError: - print("pyautogui not installed. Run: pip install pyautogui") - except Exception as e: - print(f"Error sending keyboard shortcut {keys}: {e}") - -def pause_video(): - """Click center and press Space to pause/play video.""" - try: - import pyautogui - screen_width, screen_height = pyautogui.size() - x = screen_width // 2 - y = screen_height // 2 - pyautogui.moveTo(x, y, duration=0.3) - pyautogui.click() # Focus player - time.sleep(0.2) - pyautogui.press("space") # Use spacebar instead of 'k' - print("āÆļø Sent 'space' to pause/play video") - except Exception as e: - print(f"āš ļø pause_video error: {e}") - - - - -def _send_single_key(key): - try: - import pyautogui - pyautogui.press(key) - except ImportError: - print("pyautogui not installed. Run: pip install pyautogui") - except Exception as e: - print(f"Error sending key '{key}': {e}") - -def swipe_left_tab(): - """Three-finger swipe left = switch to previous tab (Mac).""" - if OS == "Darwin": - os.system("""osascript -e 'tell application "System Events" to key code 123 using control down'""") # Left arrow - -def swipe_right_tab(): - """Three-finger swipe right = switch to next tab (Mac).""" - if OS == "Darwin": - os.system("""osascript -e 'tell application "System Events" to key code 124 using control down'""") # Right arrow - -import pyautogui - -def start_presentation(): - """Start PowerPoint presentation (equivalent to pressing F5).""" - try: - pyautogui.press("f5") - print("šŸ“½ Started presentation") - except Exception as e: - print(f"āš ļø Error starting presentation: {e}") - -def next_slide(): - """Go to the next PowerPoint slide.""" - try: - pyautogui.press("right") - print("āž”ļø Next slide") - except Exception as e: - print(f"āš ļø Error moving to next slide: {e}") - -def previous_slide(): - """Go to the previous PowerPoint slide.""" - try: - pyautogui.press("left") - print("ā¬…ļø Previous slide") - except Exception as e: - print(f"āš ļø Error moving to previous slide: {e}") - -def exit_presentation(): - """Exits PowerPoint slideshow by bringing it to front and sending ESC.""" - try: - import pyautogui - import os - import time - - # Step 1: Bring PowerPoint to the foreground - os.system('osascript -e \'tell application "Microsoft PowerPoint" to activate\'') - time.sleep(0.5) # Let the window come to front - - # Step 2: Send ESC key to exit slideshow - pyautogui.press("esc") - print("šŸ›‘ Exited PowerPoint presentation") - - except Exception as e: - print(f"āš ļø Error exiting PowerPoint: {e}") - - - - - - - -# -------------------------------------------- -# Gesture to Action Mapping -# -------------------------------------------- - -contexts = { - "default": { - "open_palm": paste, - "fist": open_terminal, - "thumbs_up": open_browser, - "ok_sign": lock_computer, - "thumbs_down": open_file_explorer, - "three_fingers": None, - "rock_on": None, - "pinch": pause_video, - "swipe_left": swipe_left_tab, - "swipe_right": swipe_right_tab - }, - "word_mode": { - "pointing_finger": select_all, - "open_palm": paste, - "peace_sign": copy, - "fist": cut, - "thumbs_up": undo, - "thumbs_down": redo, - "three_fingers": None, - "rock_on": None - }, - "media_mode": { - "pinch": pause_video, - "swipe_left": decrease_volume, - "swipe_right": increase_volume, - "three_fingers": None, - "rock_on": None - }, - "presentation_mode": { - "open_palm": start_presentation, - "swipe_right": next_slide, - "swipe_left": previous_slide, - "three_fingers": exit_presentation - } -} diff --git a/config.py b/config.py new file mode 100644 index 0000000..b16a3ae --- /dev/null +++ b/config.py @@ -0,0 +1,109 @@ +import streamlit as st +import json +import os +import inspect +import src.actions as actions +import src.crud as crud +import sys +import pandas as pd +from dotenv import load_dotenv +load_dotenv() + +GESTURE_INDEX_MAP_PATH = os.environ["GESTURAI_GESTURE_INDEX_MAP_PATH"] +GESTURE_ACTION_MAP_PATH = os.environ["GESTURAI_GESTURE_ACTION_MAP_PATH"] +GESTURE_DATA_PATH = os.environ["GESTURAI_GESTURE_DATA_PATH"] +GESTURE_MODEL_PATH = os.environ["GESTURAI_GESTURE_MODEL_PATH"] + +DEFAULT_GESTURE_INDEX_MAP_PATH = os.environ["GESTURAI_DEFAULT_GESTURE_INDEX_MAP_PATH"] +DEFAULT_GESTURE_ACTION_MAP_PATH = os.environ["GESTURAI_DEFAULT_GESTURE_ACTION_MAP_PATH"] +DEFAULT_GESTURE_DATA_PATH = os.environ["GESTURAI_DEFAULT_GESTURE_DATA_PATH"] +DEFAULT_GESTURE_MODEL_PATH = os.environ["GESTURAI_DEFAULT_GESTURE_MODEL_PATH"] + + +# Load current and default values for gesture-action maps and gesture-index maps +default_gesture_action_map, dga_load_success = crud.load_json_mapping(DEFAULT_GESTURE_ACTION_MAP_PATH) +if dga_load_success != True: + print(f'Error loading default gesture action map from {DEFAULT_GESTURE_ACTION_MAP_PATH}.') + sys.exit(-1) + +gesture_action_map, ga_load_success = crud.load_json_mapping(GESTURE_ACTION_MAP_PATH) +if ga_load_success != True: + print(f'Error loading gesture action map from {GESTURE_ACTION_MAP_PATH}.') + sys.exit(-1) + +default_gesture_index_map, dgi_load_success = crud.load_json_mapping(DEFAULT_GESTURE_INDEX_MAP_PATH) +if dgi_load_success != True: + print(f'Error loading default gesture index map from {DEFAULT_GESTURE_INDEX_MAP_PATH}.') + sys.exit(-1) + +gesture_index_map, gi_load_success = crud.load_json_mapping(GESTURE_INDEX_MAP_PATH) +if gi_load_success != True: + print(f'Error loading gesture index map from {GESTURE_INDEX_MAP_PATH}.') + sys.exit(-1) + +# TODO check for existence of data and model files + + + +# List available action functions +def list_actions(): + return [name for name, obj in inspect.getmembers(actions, inspect.isfunction) + if not name.startswith("_")] + +# UI starts here +st.set_page_config(page_title="Gesture Mapper UI", layout="centered") +st.title("šŸ–ļø Gesture-to-Action Mapper") + +modes = list(gesture_action_map.keys()) +actions_list = list_actions() + +st.sidebar.header("Select Mode") +selected_mode = st.sidebar.selectbox("Context Mode", modes) + +st.subheader(f"Mappings in `{selected_mode}` mode") +if gesture_action_map[selected_mode]: + for gesture, action in list(gesture_action_map[selected_mode].items()): + col1, col2, col3 = st.columns([3, 3, 1]) + with col1: + st.text(gesture) + with col2: + st.text(action) + with col3: + if st.button("āŒ", key=f"del-{selected_mode}-{gesture}"): + # TODO fix this + del gesture_action_map[selected_mode][gesture] + # save_mapping(gesture_action_map) + st.rerun() +else: + st.info("No gestures mapped yet in this mode.") + +st.markdown("---") +st.subheader("āž• Add / Update Mapping") +gesture_input = st.text_input("Gesture Name (e.g., fist, peace_sign)") +action_input = st.selectbox("Select Action", actions_list) + +if st.button("Save Mapping"): + if gesture_input: + gesture_action_map[selected_mode][gesture_input.strip()] = action_input + # save_mapping(gesture_action_map) + st.success(f"Mapped '{gesture_input}' ā†’ '{action_input}' in {selected_mode} mode") + st.rerun() + else: + st.warning("Please enter a gesture name.") + +st.markdown("---") +if st.button("šŸ” Reset to Default Mappings, Data, and Model"): + # TODO spin this out to a crud restore-defaults function + # TODO Confirm data and model exist before deleting + + # TODO Delete current gesture data, model, and mapping files + + # Save default gesture data, model, and mapping files as current + crud.save_json_mapping(GESTURE_ACTION_MAP_PATH, default_gesture_action_map) + crud.save_json_mapping(GESTURE_INDEX_MAP_PATH, default_gesture_index_map) + + + + + + diff --git a/gesture_config.json b/configs/archive/default_gesture_action_map.json similarity index 63% rename from gesture_config.json rename to configs/archive/default_gesture_action_map.json index 401516e..d206c8a 100644 --- a/gesture_config.json +++ b/configs/archive/default_gesture_action_map.json @@ -1,35 +1,46 @@ -{ - "default": { +{ + "mode_context_selection" : { + "three_fingers": "mode_word", + "peace_sign": "mode_media", + "ok_sign": "mode_presentation", + "rock_on": "mode_default" + }, + + "mode_default": { "open_palm": "paste", "fist": "open_terminal", "thumbs_up": "open_browser", "ok_sign": "lock_computer", "thumbs_down": "open_file_explorer", "three_fingers": "None", - "rock_on": "None", + "rock_on": "mode_context_selection", "pinch": "pause_video", "swipe_left": "swipe_left_tab", "swipe_right": "swipe_right_tab" }, - "word_mode": { + + "mode_word": { + "rock_on": "mode_context_selection", "pointing_finger": "select_all", "open_palm": "paste", "peace_sign": "copy", "fist": "cut", "thumbs_up": "undo", "thumbs_down": "redo", - "three_fingers": "None", - "rock_on": "None" + "three_fingers": "None" }, - "media_mode": { + + "mode_media": { + "rock_on": "mode_context_selection", "swipe_left": "decrease_volume", "swipe_right": "increase_volume", "three_fingers": "None", - "rock_on": "None", "pinch": "pause_video", "open_palm": "pause_video" }, - "presentation_mode": { + + "mode_presentation": { + "rock_on": "mode_context_selection", "open_palm": "start_presentation", "swipe_right": "next_slide", "swipe_left": "previous_slide", diff --git a/configs/archive/default_gesture_index_map.json b/configs/archive/default_gesture_index_map.json new file mode 100644 index 0000000..ef84fdd --- /dev/null +++ b/configs/archive/default_gesture_index_map.json @@ -0,0 +1,14 @@ +{ + "open_palm": 0, + "fist": 1, + "peace_sign": 2, + "thumbs_up": 3, + "pointing_finger": 4, + "ok_sign": 5, + "thumbs_down": 6, + "three_fingers": 7, + "rock_on": 8, + "pinch": 9, + "swipe_left": 10, + "swipe_right": 11 +} \ No newline at end of file diff --git a/configs/archive/gesture_action_map.json b/configs/archive/gesture_action_map.json new file mode 100644 index 0000000..d206c8a --- /dev/null +++ b/configs/archive/gesture_action_map.json @@ -0,0 +1,49 @@ +{ + "mode_context_selection" : { + "three_fingers": "mode_word", + "peace_sign": "mode_media", + "ok_sign": "mode_presentation", + "rock_on": "mode_default" + }, + + "mode_default": { + "open_palm": "paste", + "fist": "open_terminal", + "thumbs_up": "open_browser", + "ok_sign": "lock_computer", + "thumbs_down": "open_file_explorer", + "three_fingers": "None", + "rock_on": "mode_context_selection", + "pinch": "pause_video", + "swipe_left": "swipe_left_tab", + "swipe_right": "swipe_right_tab" + }, + + "mode_word": { + "rock_on": "mode_context_selection", + "pointing_finger": "select_all", + "open_palm": "paste", + "peace_sign": "copy", + "fist": "cut", + "thumbs_up": "undo", + "thumbs_down": "redo", + "three_fingers": "None" + }, + + "mode_media": { + "rock_on": "mode_context_selection", + "swipe_left": "decrease_volume", + "swipe_right": "increase_volume", + "three_fingers": "None", + "pinch": "pause_video", + "open_palm": "pause_video" + }, + + "mode_presentation": { + "rock_on": "mode_context_selection", + "open_palm": "start_presentation", + "swipe_right": "next_slide", + "swipe_left": "previous_slide", + "three_fingers": "exit_presentation" + } +} \ No newline at end of file diff --git a/configs/archive/gesture_index_map.json b/configs/archive/gesture_index_map.json new file mode 100644 index 0000000..ef84fdd --- /dev/null +++ b/configs/archive/gesture_index_map.json @@ -0,0 +1,14 @@ +{ + "open_palm": 0, + "fist": 1, + "peace_sign": 2, + "thumbs_up": 3, + "pointing_finger": 4, + "ok_sign": 5, + "thumbs_down": 6, + "three_fingers": 7, + "rock_on": 8, + "pinch": 9, + "swipe_left": 10, + "swipe_right": 11 +} \ No newline at end of file diff --git a/configs/default_gesture_action_map.json b/configs/default_gesture_action_map.json new file mode 100644 index 0000000..fc7c980 --- /dev/null +++ b/configs/default_gesture_action_map.json @@ -0,0 +1,34 @@ +{ + "mode_context_selection" : { + "fist": "mode_word", + "peace_sign": "mode_media", + "ok_sign": "mode_presentation", + "pointing": "mode_default" + }, + + "mode_default": { + "pointing": "mode_context_selection", + "open_palm": "paste", + "fist": "open_terminal", + "thumbs_up": "open_browser", + "ok_sign": "lock_computer" + }, + + "mode_word": { + "pointing": "mode_context_selection", + "open_palm": "paste", + "peace_sign": "copy", + "fist": "cut", + "thumbs_up": "undo" + }, + + "mode_media": { + "pointing": "mode_context_selection", + "open_palm": "pause_video" + }, + + "mode_presentation": { + "pointing": "mode_context_selection", + "open_palm": "start_presentation" + } +} \ No newline at end of file diff --git a/configs/default_gesture_index_map.json b/configs/default_gesture_index_map.json new file mode 100644 index 0000000..7ed1dfa --- /dev/null +++ b/configs/default_gesture_index_map.json @@ -0,0 +1,9 @@ +{ + "open_palm": 0, + "fist": 1, + "peace_sign": 2, + "thumbs_up": 3, + "ok_sign": 4, + "pointing": 5, + "other_gesture": 6 +} \ No newline at end of file diff --git a/configs/gesture_action_map.json b/configs/gesture_action_map.json new file mode 100644 index 0000000..84dc510 --- /dev/null +++ b/configs/gesture_action_map.json @@ -0,0 +1,30 @@ +{ + "mode_context_selection": { + "fist": "mode_word", + "peace_sign": "mode_media", + "ok_sign": "mode_presentation", + "pointing": "mode_default" + }, + "mode_default": { + "pointing": "mode_context_selection", + "open_palm": "paste", + "fist": "open_terminal", + "thumbs_up": "open_browser", + "ok_sign": "lock_computer" + }, + "mode_word": { + "pointing": "mode_context_selection", + "open_palm": "paste", + "peace_sign": "copy", + "fist": "cut", + "thumbs_up": "undo" + }, + "mode_media": { + "pointing": "mode_context_selection", + "open_palm": "pause_video" + }, + "mode_presentation": { + "pointing": "mode_context_selection", + "open_palm": "start_presentation" + } +} \ No newline at end of file diff --git a/configs/gesture_index_map.json b/configs/gesture_index_map.json new file mode 100644 index 0000000..c4d3b74 --- /dev/null +++ b/configs/gesture_index_map.json @@ -0,0 +1,10 @@ +{ + "other_gesture": 0, + "fist": 1, + "peace_sign": 2, + "thumbs_up": 3, + "ok_sign": 4, + "pointing": 5, + "open_palm": 6, + "rock_on": 7 +} \ No newline at end of file diff --git a/gesture_data_backup.pkl b/data/archive/gesture_data_backup.pkl similarity index 100% rename from gesture_data_backup.pkl rename to data/archive/gesture_data_backup.pkl diff --git a/data/fist.csv b/data/fist.csv new file mode 100644 index 0000000..c47db7d --- /dev/null +++ b/data/fist.csv @@ -0,0 +1,245 @@ +handedness,0_x,0_y,0_z,1_x,1_y,1_z,2_x,2_y,2_z,3_x,3_y,3_z,4_x,4_y,4_z,5_x,5_y,5_z,6_x,6_y,6_z,7_x,7_y,7_z,8_x,8_y,8_z,9_x,9_y,9_z,10_x,10_y,10_z,11_x,11_y,11_z,12_x,12_y,12_z,13_x,13_y,13_z,14_x,14_y,14_z,15_x,15_y,15_z,16_x,16_y,16_z,17_x,17_y,17_z,18_x,18_y,18_z,19_x,19_y,19_z,20_x,20_y,20_z 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time +import os +import json +import sys +import src.gesture_model as gm +import src.actions as actions +import src.crud as crud +from dotenv import load_dotenv + + +# Load environment variables +# These should be set in the environment or a .env file +load_dotenv() +GESTURE_INDEX_MAP_PATH = os.environ["GESTURAI_GESTURE_INDEX_MAP_PATH"] +GESTURE_ACTION_MAP_PATH = os.environ["GESTURAI_GESTURE_ACTION_MAP_PATH"] +GESTURE_MODEL_PATH = os.environ["GESTURAI_GESTURE_MODEL_PATH"] + +# Load label map +gesture_index_map = crud.load_json_mapping(GESTURE_INDEX_MAP_PATH) +index_gesture_map = {v: k for k, v in gesture_index_map.items()} + +# Load gesture recognition model +# gesture_model = GestureClassifier(input_size=64, num_classes=len(gesture_index_map.keys())) +# gesture_model.load_state_dict(torch.load(GESTURE_MODEL_PATH)) +# gesture_model.eval() + +# TODO change this to load model weights only when the model is trained with weights_only = True +#load gesture model including structure from pth file +gesture_model = torch.load(GESTURE_MODEL_PATH, map_location=torch.device('cpu'), weights_only = False) + +# Load gesture-action mapping +gesture_action_map = crud.load_json_mapping(GESTURE_ACTION_MAP_PATH) + +# Initialize MediaPipe +mp_hands = mp.solutions.hands +hands = mp_hands.Hands(static_image_mode=False, max_num_hands=1, min_detection_confidence=0.3) +mp_draw = mp.solutions.drawing_utils + +# Prep main loop +active_context = "mode_context_selection" +cap = cv2.VideoCapture(0) +cooldown = 2.5 # seconds +last_trigger_time = time.time() +gesture_display = "Waiting..." + +# main loop +while cap.isOpened(): + ret, frame = cap.read() + if not ret: + break + + frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) + result = hands.process(frame_rgb) + + if result.multi_hand_landmarks: + for i in range(len(result.multi_hand_landmarks)): + + # Get the hand landmarks and handedness + hand_landmarks = result.multi_hand_landmarks[i] + handedness = 1 if result.multi_handedness[i].classification[0].label == "Right" else -1 + + # Draw hand landmarks on the frame + mp_draw.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS) + + # Extract landmarks and convert to 3D coordinates for normalization + hand_landmarks = [[landmark.x, landmark.y, landmark.z] for landmark in hand_landmarks.landmark] + + # Normalize the landmarks, returning a 1D numpy array + hand_landmarks = gm.normalize_landmarks(hand_landmarks) + + # Flatten the array to 1D + np.array(hand_landmarks).flatten() + + # Append handedness as a numeric feature for the model + features = np.append(handedness, hand_landmarks) + + # Convert to tensor & predict gesture + features = torch.tensor(features, dtype=torch.float32) + with torch.no_grad(): + gesture_output = gesture_model(features) + predicted_gesture = index_gesture_map[torch.argmax(gesture_output).item()] + print(f"Predicted gesture: {predicted_gesture}") + + try: + + # Set display text to current gesture and context + gesture_display = f"{predicted_gesture} ({active_context})" + + # Check if the gesture maps to an action in the active context + action_name = "None" + try: + action_name = gesture_action_map[active_context][predicted_gesture] + except KeyError: + print(f"āš ļø No action found for gesture '{predicted_gesture}' in '{active_context}'") + + if time.time() - last_trigger_time > cooldown and action_name != "None": + + # If the first 5 letters of the action name are "mode_" + # And the action name is one of the keys in the gesture_map (a valid context) + # Then switch the active context to the action name + if action_name[:5] == "mode_" and action_name in gesture_action_map.keys(): + print(f"šŸ”„ Context switched to: {active_context}") + active_context = gesture_action_map[active_context][predicted_gesture] + last_trigger_time = time.time() + + # Map gesture to action, and execute if applicable + else: + + try: + print(f"[ACTION] {predicted_gesture} in {active_context}") + action = getattr(actions, action_name) + action() + last_trigger_time = time.time() + except AttributeError: + print(f"āš ļø Action function '{action_name}' not found in actions.py") + + except Exception as e: + print(f"[ERROR] {e}") + else: + gesture_display = f"No hand detected ({active_context})" + + # Display gesture and context + cv2.putText(frame, f"Gesture: {gesture_display}", (20, 40), + cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2) + cv2.putText(frame, f"Mode: {active_context}", (20, 80), + cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 0), 2) + + cv2.imshow("GesturAI", frame) + + if cv2.waitKey(1) & 0xFF == ord('q'): + break + +cap.release() +cv2.destroyAllWindows() diff --git a/gesture_mapping.py b/gesture_mapping.py deleted file mode 100644 index 9ad2045..0000000 --- a/gesture_mapping.py +++ /dev/null @@ -1,32 +0,0 @@ -import json -import os -import actions # your existing actions.py module - -CONFIG_PATH = "gesture_config.json" - -def load_gesture_mapping(): - if not os.path.exists(CONFIG_PATH): - print("āš ļø No config file found, using default empty mapping.") - return {} - - with open(CONFIG_PATH, "r") as f: - return json.load(f) - -def get_action_from_gesture(gesture, mode, mapping): - """Returns the callable action function for a given gesture and mode.""" - try: - action_name = mapping[mode][gesture] - return getattr(actions, action_name) - except KeyError: - print(f"āš ļø No action found for gesture '{gesture}' in mode '{mode}'") - return None - except AttributeError: - print(f"āš ļø Action function '{action_name}' not found in actions.py") - return None - -# Example usage: -if __name__ == "__main__": - gesture_map = load_gesture_mapping() - action = get_action_from_gesture("fist", "default", gesture_map) - if action: - action() diff --git a/gesture_ui_mapper.py b/gesture_ui_mapper.py deleted file mode 100644 index a031bac..0000000 --- a/gesture_ui_mapper.py +++ /dev/null @@ -1,108 +0,0 @@ -import streamlit as st -import json -import os -import inspect -import actions - -CONFIG_PATH = "gesture_config.json" -DEFAULT_MAPPING = { - "default": { - "open_palm": "paste", - "fist": "open_terminal", - "thumbs_up": "open_browser", - "ok_sign": "lock_computer", - "thumbs_down": "open_file_explorer", - "three_fingers": "None", - "rock_on": "None", - "pinch": "pause_video", - "swipe_left": "swipe_left_tab", - "swipe_right": "swipe_right_tab" - }, - "word_mode": { - "pointing_finger": "select_all", - "open_palm": "paste", - "peace_sign": "copy", - "fist": "cut", - "thumbs_up": "undo", - "thumbs_down": "redo", - "three_fingers": "None", - "rock_on": "None" - }, - "media_mode": { - "swipe_left": "decrease_volume", - "swipe_right": "increase_volume", - "three_fingers": "None", - "rock_on": "None", - "pinch": "pause_video", - "open_palm": "pause_video" - }, - "presentation_mode": { - "open_palm": "start_presentation", - "swipe_right": "next_slide", - "swipe_left": "previous_slide", - "three_fingers": "exit_presentation" - } -} - -# Utility to load and save mapping -def load_mapping(): - if os.path.exists(CONFIG_PATH): - with open(CONFIG_PATH, "r") as f: - return json.load(f) - return DEFAULT_MAPPING.copy() - -def save_mapping(mapping): - with open(CONFIG_PATH, "w") as f: - json.dump(mapping, f, indent=2) - -# List available action functions -def list_actions(): - return [name for name, obj in inspect.getmembers(actions, inspect.isfunction) - if not name.startswith("_")] - -# UI starts here -st.set_page_config(page_title="Gesture Mapper UI", layout="centered") -st.title("šŸ–ļø Gesture-to-Action Mapper") - -mapping = load_mapping() -modes = list(mapping.keys()) -actions_list = list_actions() - -st.sidebar.header("Select Mode") -selected_mode = st.sidebar.selectbox("Context Mode", modes) - -st.subheader(f"Mappings in `{selected_mode}` mode") -if mapping[selected_mode]: - for gesture, action in list(mapping[selected_mode].items()): - col1, col2, col3 = st.columns([3, 3, 1]) - with col1: - st.text(gesture) - with col2: - st.text(action) - with col3: - if st.button("āŒ", key=f"del-{selected_mode}-{gesture}"): - del mapping[selected_mode][gesture] - save_mapping(mapping) - st.rerun() -else: - st.info("No gestures mapped yet in this mode.") - -st.markdown("---") -st.subheader("āž• Add / Update Mapping") -gesture_input = st.text_input("Gesture Name (e.g., fist, peace_sign)") -action_input = st.selectbox("Select Action", actions_list) - -if st.button("Save Mapping"): - if gesture_input: - mapping[selected_mode][gesture_input.strip()] = action_input - save_mapping(mapping) - st.success(f"Mapped '{gesture_input}' ā†’ '{action_input}' in {selected_mode} mode") - st.rerun() - else: - st.warning("Please enter a gesture name.") - -st.markdown("---") -if st.button("šŸ” Reset to Default Mappings"): - save_mapping(DEFAULT_MAPPING.copy()) - st.success("Mappings reset to default.") - st.rerun() \ No newline at end of file diff --git a/model.py b/model.py deleted file mode 100644 index 9554940..0000000 --- a/model.py +++ /dev/null @@ -1,15 +0,0 @@ -import torch.nn as nn - -class GestureClassifier(nn.Module): - def __init__(self, input_size, num_classes): - super(GestureClassifier, self).__init__() - self.fc1 = nn.Linear(input_size, 128) - self.fc2 = nn.Linear(128, 64) - self.fc3 = nn.Linear(64, num_classes) - self.relu = nn.ReLU() - - def forward(self, x): - x = self.relu(self.fc1(x)) - x = self.relu(self.fc2(x)) - x = self.fc3(x) - return x diff --git a/models/archive/gesture_model_lasya.pth b/models/archive/gesture_model_lasya.pth new file mode 100644 index 0000000..fbe368c Binary files /dev/null and b/models/archive/gesture_model_lasya.pth differ diff --git a/models/archive/gesture_model_neal.pth b/models/archive/gesture_model_neal.pth new file mode 100644 index 0000000..34ce075 Binary files /dev/null and b/models/archive/gesture_model_neal.pth differ diff --git a/notebook.ipynb b/notebook.ipynb new file mode 100644 index 0000000..39f0bc4 --- /dev/null +++ b/notebook.ipynb @@ -0,0 +1,1662 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test Load Gesture Data\n", + "import src.crud as crud\n", + "\n", + "data_path = \"data/\"\n", + "\n", + "df = crud.load_gesture_data(\n", + " data_path = data_path,\n", + " gesture_name = 'other_gesture',\n", + " suffix = '.csv')\n", + "\n", + "print(str(df.shape))\n", + "\n", + "df.head()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Test Data Capture" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test gesture data capture\n", + "import gesture_data as gdc\n", + "data_path = \"data/\"\n", + "gesture_name = \"other_gesture\"\n", + "df = gdc.gather_gesture_data(\n", + " gesture_name=gesture_name,\n", + ")\n", + "df.to_csv(data_path+gesture_name+'.csv', index=False)\n", + "df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Test Model Training" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Train a model\n", + "import gesture_model as gm\n", + "import pandas as pd\n", + "import src.crud as crud\n", + "import pickle\n", + "\n", + "data_path = \"data/\"\n", + "model_path = \"models/\"\n", + "\n", + "# load the data and gesture-index map\n", + "df = crud.load_concat_csvs(data_path = data_path)\n", + "gesture_index_map, success = crud.load_json_mapping(\n", + " \"configs/gesture_index_map.json\"\n", + ")\n", + "\n", + "# Drop all rows with any nulls - shouldn't be any\n", + "df = df.dropna()\n", + "\n", + "# Create new feature y based on gesture index map\n", + "df['y'] = df['gesture_name'].map(gesture_index_map)\n", + "df = df.drop(columns=[\"gesture_name\", \"capture_number\",\"score\"])\n", + "\n", + "# Get a balanced sample of the data\n", + "df = gm.get_balanced_sample(\n", + " df,\n", + " 100, \n", + " 300)[0]\n", + "\n", + "\n", + "\n", + "# Normalize hand landmarks\n", + "df = gm.normalize_landmarks_df(df)\n", + "\n", + "print(df.columns)\n", + "\n", + "# train the model\n", + "model = gm.model_training_pipeline(df)\n", + "\n", + "import torch\n", + "# Save the model using PyTorch's save function\n", + "torch.save(model, model_path + \"gesture_model.pth\")\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Test Add/Remove/Rename Contexts" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test crud - add context\n", + "import src.crud as crud\n", + "crud.create_context(\n", + " 'mode_TEST',\n", + " 'configs/gesture_action_map.json')\n", + "\n", + "gesture_action_map = crud.load_json_mapping(\n", + " \"configs/gesture_action_map.json\"\n", + ")\n", + "print(gesture_action_map)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test crud - remove context\n", + "import src.crud as crud\n", + "crud.delete_context(\n", + " 'mode_TEST',\n", + " 'configs/gesture_action_map.json')\n", + "\n", + "gesture_action_map = crud.load_json_mapping(\n", + " \"configs/gesture_action_map.json\"\n", + ")\n", + "print(gesture_action_map)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test crud - rename context\n", + "import src.crud as crud\n", + "crud.rename_context(\n", + " 'mode_presentation',\n", + " 'mode_presentation_renamed',\n", + " 'configs/gesture_action_map.json'\n", + ")\n", + "\n", + "gesture_action_map = crud.load_json_mapping(\n", + " \"configs/gesture_action_map.json\"\n", + ")\n", + "print(gesture_action_map)\n", + "\n", + "# Clean up the name\n", + "crud.rename_context(\n", + " 'mode_presentation_renamed',\n", + " 'mode_presentation',\n", + " 'configs/gesture_action_map.json'\n", + ")\n", + "\n", + "gesture_action_map = crud.load_json_mapping(\n", + " \"configs/gesture_action_map.json\"\n", + ")\n", + "print(gesture_action_map)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Test Create/Delete Gesture-Action Mapping" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test crud - create gesture-action mapping\n", + "import src.crud as crud\n", + "import src.actions as actions\n", + "import random\n", + "\n", + "actions_list = actions.get_actions_list()\n", + "\n", + "gesture_list = list(crud.load_json_mapping(\n", + " \"configs/gesture_index_map.json\"\n", + ").keys())\n", + "\n", + "random_action = random.choice(actions_list)\n", + "random_gesture = random.choice(gesture_list)\n", + "\n", + "crud.create_context(\n", + " 'mode_TEST', # test context\n", + " 'configs/gesture_action_map.json')\n", + "print(crud.load_json_mapping(\"configs/gesture_action_map.json\"))\n", + "\n", + "\n", + "crud.create_gesture_action_mapping(\n", + " random_gesture,\n", + " random_action,\n", + " 'mode_TEST',\n", + " 'configs/gesture_action_map.json'\n", + ")\n", + "print(crud.load_json_mapping(\"configs/gesture_action_map.json\"))\n", + "\n", + "crud.delete_gesture_action_mapping(\n", + " random_gesture,\n", + " random_action,\n", + " 'mode_TEST',\n", + " 'configs/gesture_action_map.json'\n", + ")\n", + "print(crud.load_json_mapping(\"configs/gesture_action_map.json\"))\n", + "\n", + "\n", + "crud.delete_context(\n", + " 'mode_TEST',\n", + " 'configs/gesture_action_map.json'\n", + ")\n", + "print(crud.load_json_mapping(\"configs/gesture_action_map.json\"))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Test Add/Retrain/Rename/Delete Gesture" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Press 'c' to capture current landmarks\n", + "Press 'r' reset captured landmarks\n", + "Press 's' to save the captured landmarks\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\haits\\projects\\GesturAI\\src\\gesture_data.py:109: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n", + " landmarks_df = pd.concat([landmarks_df, pd.DataFrame([current_item])], ignore_index=True)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand 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"output_type": "stream", + "text": [ + "c:\\Users\\haits\\projects\\GesturAI\\src\\gesture_model.py:128: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n", + " df_balanced = pd.concat([df_balanced, subsample], ignore_index=True)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/57, Training Loss: 2.2130\n", + "\n", + "āœ… Test Accuracy: 14.72%\n", + "Epoch 2/57, Training Loss: 2.1762\n", + "\n", + "āœ… Test Accuracy: 29.72%\n", + "Epoch 3/57, Training Loss: 2.1432\n", + "\n", + "āœ… Test Accuracy: 46.39%\n", + "Epoch 4/57, Training Loss: 2.1078\n", + "\n", + "āœ… Test Accuracy: 60.56%\n", + "Epoch 5/57, Training Loss: 2.0691\n", + "\n", + "āœ… Test Accuracy: 69.72%\n", + "Epoch 6/57, Training Loss: 2.0269\n", + "\n", + "āœ… Test Accuracy: 73.33%\n", + "Epoch 7/57, Training Loss: 1.9802\n", + "\n", + "āœ… Test Accuracy: 73.06%\n", + "Epoch 8/57, Training Loss: 1.9279\n", + "\n", + "āœ… Test Accuracy: 72.22%\n", + "Epoch 9/57, Training Loss: 1.8696\n", + "\n", + "āœ… Test Accuracy: 72.22%\n", + "Epoch 10/57, Training 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"text/plain": [ + "True" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "import src.crud as crud\n", + "import os\n", + "from dotenv import load_dotenv\n", + "load_dotenv()\n", + "\n", + "crud.create_gesture(\n", + " 'three_fingers',\n", + " os.getenv('GESTURAI_GESTURE_INDEX_MAP_PATH'),\n", + " os.getenv('GESTURAI_GESTURE_DATA_PATH'),\n", + " os.getenv('GESTURAI_GESTURE_MODEL_PATH'),\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Press 'c' to capture current landmarks\n", + "Press 'r' reset captured landmarks\n", + "Press 's' to save the captured landmarks\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\haits\\projects\\GesturAI\\src\\gesture_data.py:109: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n", + " landmarks_df = pd.concat([landmarks_df, pd.DataFrame([current_item])], ignore_index=True)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand landmarks\n", + "Frame captured with hand 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In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n", + " df_balanced = pd.concat([df_balanced, subsample], ignore_index=True)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/57, Training Loss: 2.2029\n", + "\n", + "āœ… Test Accuracy: 30.28%\n", + "Epoch 2/57, Training Loss: 2.1629\n", + "\n", + "āœ… Test Accuracy: 46.39%\n", + "Epoch 3/57, Training Loss: 2.1257\n", + "\n", + "āœ… Test Accuracy: 49.44%\n", + "Epoch 4/57, Training Loss: 2.0863\n", + "\n", + "āœ… Test Accuracy: 60.28%\n", + "Epoch 5/57, Training Loss: 2.0441\n", + "\n", + "āœ… Test Accuracy: 66.11%\n", + "Epoch 6/57, Training Loss: 1.9980\n", + "\n", + "āœ… Test Accuracy: 65.83%\n", + "Epoch 7/57, Training Loss: 1.9473\n", + "\n", + "āœ… Test Accuracy: 66.39%\n", + "Epoch 8/57, Training Loss: 1.8910\n", + "\n", + "āœ… Test Accuracy: 65.56%\n", + "Epoch 9/57, Training Loss: 1.8287\n", + "\n", + "āœ… Test Accuracy: 68.89%\n", + "Epoch 10/57, Training 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"text/plain": [ + "True" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "import src.crud as crud\n", + "import os\n", + "from dotenv import load_dotenv\n", + "load_dotenv()\n", + "\n", + "crud.retrain_gesture(\n", + " 'three_fingers',\n", + " os.getenv('GESTURAI_GESTURE_INDEX_MAP_PATH'),\n", + " os.getenv('GESTURAI_GESTURE_DATA_PATH'),\n", + " os.getenv('GESTURAI_GESTURE_MODEL_PATH'),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "import src.crud as crud\n", + "import os\n", + "from dotenv import load_dotenv\n", + "load_dotenv()\n", + "\n", + "# TODO problem - doesn't rename the gesture within the data file - but this is extraneous\n", + "crud.rename_gesture(\n", + " current_gesture_name = 'three_fingers',\n", + " new_gesture_name = 'thumbs_down',\n", + " gesture_index_map_path = os.getenv('GESTURAI_GESTURE_INDEX_MAP_PATH'),\n", + " gesture_action_map_path= os.getenv('GESTURAI_GESTURE_ACTION_MAP_PATH'),\n", + " gesture_data_path = os.getenv('GESTURAI_GESTURE_DATA_PATH'),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Gesture index map: {'other_gesture': 0, 'fist': 1, 'peace_sign': 2, 'thumbs_up': 3, 'ok_sign': 4, 'pointing': 5, 'open_palm': 6, 'rock_on': 7}\n", + "Gesture action map: {'mode_context_selection': {'fist': 'mode_word', 'peace_sign': 'mode_media', 'ok_sign': 'mode_presentation', 'pointing': 'mode_default'}, 'mode_default': {'pointing': 'mode_context_selection', 'open_palm': 'paste', 'fist': 'open_terminal', 'thumbs_up': 'open_browser', 'ok_sign': 'lock_computer'}, 'mode_word': {'pointing': 'mode_context_selection', 'open_palm': 'paste', 'peace_sign': 'copy', 'fist': 'cut', 'thumbs_up': 'undo'}, 'mode_media': {'pointing': 'mode_context_selection', 'open_palm': 'pause_video'}, 'mode_presentation': {'pointing': 'mode_context_selection', 'open_palm': 'start_presentation'}}\n", + "Training data: handedness 0_x 0_y 0_z 1_x 1_y \\\n", + "0 Right 0.742718 0.951670 -3.220000e-07 0.703873 0.903941 \n", + "1 Right 0.747208 0.937961 -3.160000e-07 0.708615 0.891739 \n", + "2 Right 0.761541 0.919692 -2.140000e-07 0.720827 0.872689 \n", + "3 Right 0.770514 0.904924 -1.790000e-07 0.727406 0.864357 \n", + "4 Right 0.772167 0.889240 -2.020000e-07 0.728882 0.857308 \n", + "... ... ... ... ... ... ... \n", + "2464 Left 0.266856 0.893311 4.040000e-09 0.307233 0.854793 \n", + "2465 Left 0.277808 0.867316 2.320000e-08 0.320736 0.825004 \n", + "2466 Left 0.292914 0.846023 5.480000e-08 0.334654 0.802904 \n", + "2467 Left 0.279110 0.844525 2.210000e-08 0.321710 0.806802 \n", + "2468 Left 0.245450 0.856683 3.440000e-08 0.289460 0.820132 \n", + "\n", + " 1_z 2_x 2_y 2_z ... 18_x 18_y \\\n", + "0 -0.014537 0.673273 0.844208 -0.029780 ... 0.766893 0.806165 \n", + "1 -0.014757 0.678166 0.829213 -0.028881 ... 0.776387 0.791887 \n", + "2 -0.015426 0.691903 0.800460 -0.030212 ... 0.806679 0.762213 \n", + "3 -0.015827 0.695139 0.793421 -0.032589 ... 0.813394 0.745947 \n", + "4 -0.017244 0.696078 0.789550 -0.035743 ... 0.814799 0.729928 \n", + "... ... ... ... ... ... ... ... \n", + "2464 -0.011469 0.345622 0.791331 -0.020277 ... 0.226607 0.653423 \n", + "2465 -0.009469 0.355241 0.764126 -0.016632 ... 0.245711 0.625392 \n", + "2466 -0.010484 0.366856 0.744563 -0.018489 ... 0.264412 0.606877 \n", + "2467 -0.009264 0.353951 0.747012 -0.014485 ... 0.257546 0.601410 \n", + "2468 -0.013066 0.325620 0.761909 -0.022335 ... 0.210299 0.620495 \n", + "\n", + " 18_z 19_x 19_y 19_z 20_x 20_y 20_z \\\n", + "0 -0.069204 0.733184 0.827431 -0.071471 0.711158 0.851519 -0.067495 \n", + "1 -0.064201 0.743184 0.810745 -0.066286 0.721078 0.832622 -0.062334 \n", + "2 -0.078503 0.780875 0.770459 -0.082011 0.760476 0.787182 -0.079727 \n", + "3 -0.094691 0.788426 0.752001 -0.100521 0.767376 0.769264 -0.100117 \n", + "4 -0.102500 0.789841 0.736884 -0.109664 0.769487 0.754254 -0.110459 \n", + "... ... ... ... ... ... ... ... \n", + "2464 -0.057529 0.225012 0.647324 -0.060284 0.220523 0.626176 -0.057653 \n", + "2465 -0.045784 0.246681 0.604318 -0.048279 0.245944 0.572319 -0.045884 \n", + "2466 -0.039980 0.266382 0.582442 -0.042004 0.268287 0.545699 -0.039941 \n", + "2467 -0.034726 0.261288 0.575935 -0.036343 0.265848 0.543503 -0.034311 \n", + "2468 -0.051035 0.207812 0.593747 -0.053267 0.206530 0.565609 -0.050378 \n", + "\n", + " gesture_name \n", + "0 other_gesture \n", + "1 other_gesture \n", + "2 other_gesture \n", + "3 other_gesture \n", + "4 other_gesture \n", + "... ... \n", + "2464 rock_on \n", + "2465 rock_on \n", + "2466 rock_on \n", + "2467 rock_on \n", + "2468 rock_on \n", + "\n", + "[2469 rows x 65 columns]\n", + "Training data shape: (2469, 65)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\haits\\projects\\GesturAI\\src\\gesture_model.py:128: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n", + " df_balanced = pd.concat([df_balanced, subsample], ignore_index=True)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/54, Training Loss: 2.0677\n", + "\n", + "āœ… Test Accuracy: 22.50%\n", + "Epoch 2/54, Training Loss: 2.0288\n", + "\n", + "āœ… Test Accuracy: 35.31%\n", + "Epoch 3/54, Training Loss: 1.9916\n", + "\n", + "āœ… Test Accuracy: 53.75%\n", + "Epoch 4/54, Training Loss: 1.9518\n", + "\n", + "āœ… Test Accuracy: 60.00%\n", + "Epoch 5/54, Training Loss: 1.9083\n", + "\n", + "āœ… Test Accuracy: 65.94%\n", + "Epoch 6/54, Training Loss: 1.8603\n", + "\n", + "āœ… Test Accuracy: 71.25%\n", + "Epoch 7/54, Training Loss: 1.8070\n", + "\n", + "āœ… Test Accuracy: 74.69%\n", + "Epoch 8/54, Training Loss: 1.7479\n", + "\n", + "āœ… Test Accuracy: 75.94%\n", + "Epoch 9/54, Training Loss: 1.6829\n", + "\n", + "āœ… Test Accuracy: 78.75%\n", + "Epoch 10/54, Training 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Loss: 0.6611\n", + "\n", + "āœ… Test Accuracy: 94.06%\n", + "Epoch 23/54, Training Loss: 0.6003\n", + "\n", + "āœ… Test Accuracy: 95.00%\n", + "Epoch 24/54, Training Loss: 0.5446\n", + "\n", + "āœ… Test Accuracy: 95.62%\n", + "Epoch 25/54, Training Loss: 0.4939\n", + "\n", + "āœ… Test Accuracy: 95.62%\n", + "Epoch 26/54, Training Loss: 0.4479\n", + "\n", + "āœ… Test Accuracy: 96.25%\n", + "Epoch 27/54, Training Loss: 0.4064\n", + "\n", + "āœ… Test Accuracy: 96.88%\n", + "Epoch 28/54, Training Loss: 0.3690\n", + "\n", + "āœ… Test Accuracy: 96.88%\n", + "Epoch 29/54, Training Loss: 0.3354\n", + "\n", + "āœ… Test Accuracy: 96.88%\n", + "Epoch 30/54, Training Loss: 0.3051\n", + "\n", + "āœ… Test Accuracy: 96.88%\n", + "Epoch 31/54, Training Loss: 0.2779\n", + "\n", + "āœ… Test Accuracy: 97.50%\n", + "Epoch 32/54, Training Loss: 0.2533\n", + "\n", + "āœ… Test Accuracy: 97.81%\n", + "Epoch 33/54, Training Loss: 0.2309\n", + "\n", + "āœ… Test Accuracy: 98.12%\n", + "Epoch 34/54, Training Loss: 0.2105\n", + "\n", + "āœ… Test Accuracy: 98.44%\n", + "Epoch 35/54, Training Loss: 0.1920\n", + "\n", + "āœ… Test Accuracy: 98.44%\n", + "Epoch 36/54, Training Loss: 0.1752\n", + "\n", + "āœ… Test Accuracy: 98.44%\n", + "Epoch 37/54, Training Loss: 0.1600\n", + "\n", + "āœ… Test Accuracy: 98.44%\n", + "Epoch 38/54, Training Loss: 0.1463\n", + "\n", + "āœ… Test Accuracy: 98.44%\n", + "Epoch 39/54, Training Loss: 0.1340\n", + "\n", + "āœ… Test Accuracy: 98.44%\n", + "Epoch 40/54, Training Loss: 0.1230\n", + "\n", + "āœ… Test Accuracy: 98.44%\n", + "Epoch 41/54, Training Loss: 0.1131\n", + "\n", + "āœ… Test Accuracy: 98.44%\n", + "Epoch 42/54, Training Loss: 0.1043\n", + "\n", + "āœ… Test Accuracy: 98.75%\n", + "Epoch 43/54, Training Loss: 0.0965\n", + "\n", + "āœ… Test Accuracy: 98.75%\n", + "Epoch 44/54, Training Loss: 0.0894\n", + "\n", + "āœ… Test Accuracy: 98.75%\n", + "Epoch 45/54, Training Loss: 0.0830\n", + "\n", + "āœ… Test Accuracy: 98.75%\n", + "Epoch 46/54, Training Loss: 0.0772\n", + "\n", + "āœ… Test Accuracy: 98.75%\n", + "Epoch 47/54, Training Loss: 0.0720\n", + "\n", + "āœ… Test Accuracy: 98.75%\n", + "Epoch 48/54, Training Loss: 0.0672\n", + "\n", + "āœ… Test Accuracy: 99.06%\n", + "Epoch 49/54, Training Loss: 0.0628\n", + "\n", + "āœ… Test Accuracy: 99.06%\n", + "Epoch 50/54, Training Loss: 0.0587\n", + "\n", + "āœ… Test Accuracy: 99.06%\n", + "Epoch 51/54, Training Loss: 0.0550\n", + "\n", + "āœ… Test Accuracy: 99.06%\n", + "Epoch 52/54, Training Loss: 0.0516\n", + "\n", + "āœ… Test Accuracy: 99.06%\n", + "Epoch 53/54, Training Loss: 0.0485\n", + "\n", + "āœ… Test Accuracy: 99.06%\n", + "Epoch 54/54, Training Loss: 0.0456\n", + "\n", + "āœ… Test Accuracy: 99.06%\n" + ] + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "import src.crud as crud\n", + "import os\n", + "from dotenv import load_dotenv\n", + "load_dotenv()\n", + "\n", + "crud.delete_gesture(\n", + " deleted_gesture_name = 'thumbs_down',\n", + " gesture_index_map_path = os.getenv('GESTURAI_GESTURE_INDEX_MAP_PATH'),\n", + " gesture_action_map_path= os.getenv('GESTURAI_GESTURE_ACTION_MAP_PATH'),\n", + " gesture_data_path = os.getenv('GESTURAI_GESTURE_DATA_PATH'),\n", + " gesture_model_path = os.getenv('GESTURAI_GESTURE_MODEL_PATH'),\n", + ")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/requirements.txt b/requirements.txt index 5085fc1..41eec94 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,79 +1,15 @@ -absl-py==2.1.0 -altair==5.5.0 -attrs==25.1.0 -blinker==1.9.0 -cachetools==5.5.2 -certifi==2025.1.31 -cffi==1.17.1 -charset-normalizer==3.4.1 -click==8.1.8 -contourpy==1.3.1 -cycler==0.12.1 -filelock==3.18.0 -flatbuffers==25.1.24 -fonttools==4.56.0 -fsspec==2025.3.2 -gitdb==4.0.12 -GitPython==3.1.44 -idna==3.10 -jax==0.4.38 -jaxlib==0.4.38 -Jinja2==3.1.6 -joblib==1.4.2 jsonschema==4.23.0 jsonschema-specifications==2024.10.1 -kiwisolver==1.4.8 -MarkupSafe==3.0.2 matplotlib==3.10.0 mediapipe==0.10.21 -ml_dtypes==0.5.1 -MouseInfo==0.1.3 -mpmath==1.3.0 -narwhals==1.34.1 -networkx==3.4.2 numpy==1.26.4 opencv-contrib-python==4.11.0.86 opencv-python==4.11.0.86 -opt_einsum==3.4.0 -packaging==24.2 pandas==2.2.3 -pillow==11.1.0 -protobuf==4.25.6 -pyarrow==19.0.1 PyAutoGUI==0.9.54 -pycparser==2.22 -pydeck==0.9.1 -PyGetWindow==0.0.9 -PyMsgBox==1.0.9 -pyobjc-core==11.0 -pyobjc-framework-Cocoa==11.0 -pyobjc-framework-Quartz==11.0 -pyparsing==3.2.1 -pyperclip==1.9.0 -PyRect==0.2.0 -PyScreeze==1.0.1 -python-dateutil==2.9.0.post0 -pytweening==1.2.0 -pytz==2025.2 -referencing==0.36.2 -requests==2.32.3 -rpds-py==0.24.0 -rubicon-objc==0.5.0 scikit-learn==1.6.1 scipy==1.15.1 -sentencepiece==0.2.0 -six==1.17.0 -smmap==5.0.2 -sounddevice==0.5.1 streamlit==1.44.1 -sympy==1.13.3 -tenacity==9.1.2 -threadpoolctl==3.6.0 -toml==0.10.2 torch==2.2.2 torchaudio==2.2.2 -torchvision==0.17.2 -tornado==6.4.2 -typing_extensions==4.13.1 -tzdata==2025.2 -urllib3==2.3.0 +torchvision==0.17.2 \ No newline at end of file diff --git a/run_gesture_control.py b/run_gesture_control.py deleted file mode 100644 index 6becb41..0000000 --- a/run_gesture_control.py +++ /dev/null @@ -1,103 +0,0 @@ -import cv2 -import mediapipe as mp -import numpy as np -import torch -import pickle -import time -from model import GestureClassifier -from gesture_mapping import load_gesture_mapping, get_action_from_gesture - -# Load model -with open("label_map.pkl", "rb") as f: - label_map = pickle.load(f) # e.g., {0: 'open_palm', 1: 'fist', ...} - -model = GestureClassifier(input_size=63, num_classes=len(label_map)) -model.load_state_dict(torch.load("gesture_model.pth")) -model.eval() - -# Context switching triggers -context_triggers = { - "three_fingers": "word_mode", - "peace_sign": "media_mode", - "ok_sign": "presentation_mode", - "rock_on": "default" -} -active_context = "default" - -# Load gesture-action mapping -gesture_map = load_gesture_mapping() - -# Initialize MediaPipe -mp_hands = mp.solutions.hands -hands = mp_hands.Hands(static_image_mode=False, max_num_hands=1, min_detection_confidence=0.3) -mp_draw = mp.solutions.drawing_utils - -def normalize_keypoints(landmarks): - keypoints = np.array([(lm.x, lm.y, lm.z) for lm in landmarks]) - keypoints -= np.mean(keypoints, axis=0) - keypoints /= np.std(keypoints, axis=0) - return keypoints.flatten() - -# Webcam loop -cap = cv2.VideoCapture(0) -cooldown = 3 -last_trigger_time = 0 -gesture_display = "Waiting..." - -while cap.isOpened(): - ret, frame = cap.read() - if not ret: - break - - frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) - result = hands.process(frame_rgb) - - if result.multi_hand_landmarks: - for hand_landmarks in result.multi_hand_landmarks: - mp_draw.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS) - - try: - keypoints = normalize_keypoints(hand_landmarks.landmark) - input_tensor = torch.tensor(keypoints, dtype=torch.float32).unsqueeze(0) - output = model(input_tensor) - predicted_idx = torch.argmax(output, dim=1).item() - gesture = label_map.get(predicted_idx, "unknown") - - current_time = time.time() - gesture_display = f"{gesture} ({active_context})" - - # Handle mode switching gestures - if current_time - last_trigger_time > cooldown: - if gesture in context_triggers: - new_context = context_triggers[gesture] - if new_context != active_context: - active_context = new_context - print(f"šŸ”„ Context switched to: {active_context}") - last_trigger_time = current_time - continue - - # Use user-defined mapping - action = get_action_from_gesture(gesture, active_context, gesture_map) - if action: - print(f"[ACTION] {gesture} in {active_context}") - action() - last_trigger_time = current_time - - except Exception as e: - print(f"[ERROR] {e}") - else: - gesture_display = f"No hand detected ({active_context})" - - # Display gesture and context - cv2.putText(frame, f"Gesture: {gesture_display}", (20, 40), - cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2) - cv2.putText(frame, f"Mode: {active_context}", (20, 80), - cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 0), 2) - - cv2.imshow("GesturAI", frame) - - if cv2.waitKey(1) & 0xFF == ord('q'): - break - -cap.release() -cv2.destroyAllWindows() diff --git a/src/actions.py b/src/actions.py new file mode 100644 index 0000000..d85d131 --- /dev/null +++ b/src/actions.py @@ -0,0 +1,217 @@ +import os +import webbrowser +import platform +import subprocess +from datetime import datetime +import time +import pyautogui +import inspect + +OS = platform.system() + +def get_actions_list(): + return [name for name, obj in inspect.getmembers(action_functions) if inspect.isfunction(obj) and not name.startswith('__')] + + +class action_functions: + # -------------------------------------------- + # System Control Functions + # -------------------------------------------- + + def open_terminal(): + """Opens the terminal window based on OS.""" + try: + if OS == "Darwin": + os.system("open -a Terminal") # macOS + elif OS == "Linux": + os.system("gnome-terminal") # Linux (change if needed) + elif OS == "Windows": + os.system("start cmd") + except Exception as e: + print(f"Error opening terminal: {e}") + + def open_browser(): + """Opens the default web browser.""" + try: + webbrowser.open("https://www.google.com") + except Exception as e: + print(f"Error opening browser: {e}") + + def increase_volume(): + """Increases system volume based on OS.""" + try: + if OS == "Darwin": + os.system("osascript -e 'set volume output volume (output volume of (get volume settings) + 10)'") + elif OS == "Linux": + os.system("pactl set-sink-volume @DEFAULT_SINK@ +10%") + except Exception as e: + print(f"Error increasing volume: {e}") + + def decrease_volume(): + """Decreases system volume based on OS.""" + try: + if OS == "Darwin": + os.system("osascript -e 'set volume output volume (output volume of (get volume settings) - 10)'") + elif OS == "Linux": + os.system("pactl set-sink-volume @DEFAULT_SINK@ -10%") + except Exception as e: + print(f"Error decreasing volume: {e}") + + def take_screenshot(): + """Takes a screenshot with timestamped filename.""" + filename = f"screenshot_{datetime.now().strftime('%Y%m%d_%H%M%S')}.png" + try: + if OS == "Darwin": + os.system(f"screencapture {filename}") + elif OS == "Linux": + os.system(f"gnome-screenshot -f {filename}") + elif OS == "Windows": + os.system(f"nircmd.exe savescreenshot {filename}") # Requires nircmd.exe in PATH + except Exception as e: + print(f"Error taking screenshot: {e}") + + def lock_computer(): + """Locks the computer.""" + try: + if OS == "Windows": + os.system("rundll32.exe user32.dll,LockWorkStation") + elif OS == "Darwin": + os.system("/System/Library/CoreServices/Menu\\ Extras/User.menu/Contents/Resources/CGSession -suspend") + except Exception as e: + print(f"Error locking computer: {e}") + + def open_file_explorer(): + """Opens the file explorer.""" + try: + if OS == "Windows": + os.system("explorer") + elif OS == "Darwin": + os.system("open .") + except Exception as e: + print(f"Error opening file explorer: {e}") + + def minimize_all_windows(): + """Minimizes all windows.""" + _send_keyboard_shortcut(["win", "d"] if OS == "Windows" else ["fn", "f11"]) + + # -------------------------------------------- + # Clipboard & Editing Functions + # -------------------------------------------- + + def copy(): + _send_keyboard_shortcut(["ctrl", "c"] if OS == "Windows" else ["cmd", "c"]) + + def paste(): + _send_keyboard_shortcut(["ctrl", "v"] if OS == "Windows" else ["cmd", "v"]) + + def cut(): + _send_keyboard_shortcut(["ctrl", "x"] if OS == "Windows" else ["cmd", "x"]) + + def undo(): + _send_keyboard_shortcut(["ctrl", "z"] if OS == "Windows" else ["cmd", "z"]) + + def redo(): + _send_keyboard_shortcut(["ctrl", "y"] if OS == "Windows" else ["cmd", "shift", "z"]) + + def select_all(): + _send_keyboard_shortcut(["ctrl", "a"] if OS == "Windows" else ["cmd", "a"]) + + def save(): + _send_keyboard_shortcut(["ctrl", "s"] if OS == "Windows" else ["cmd", "s"]) + + def print_file(): + _send_keyboard_shortcut(["ctrl", "p"] if OS == "Windows" else ["cmd", "p"]) + + def find(): + _send_keyboard_shortcut(["ctrl", "f"] if OS == "Windows" else ["cmd", "f"]) + + # -------------------------------------------- + # Helper Function for Simulating Keypresses + # -------------------------------------------- + + def _send_keyboard_shortcut(keys): + try: + # macOS fix: replace 'cmd' with 'command' for pyautogui + fixed_keys = ['command' if k == 'cmd' else k for k in keys] + pyautogui.hotkey(*fixed_keys) + + except ImportError: + print("pyautogui not installed. Run: pip install pyautogui") + except Exception as e: + print(f"Error sending keyboard shortcut {keys}: {e}") + + def pause_video(): + """Click center and press Space to pause/play video.""" + try: + + screen_width, screen_height = pyautogui.size() + x = screen_width // 2 + y = screen_height // 2 + pyautogui.moveTo(x, y, duration=0.3) + pyautogui.click() # Focus player + time.sleep(0.2) + pyautogui.press("space") # Use spacebar instead of 'k' + print("āÆļø Sent 'space' to pause/play video") + except Exception as e: + print(f"āš ļø pause_video error: {e}") + + + def _send_single_key(key): + try: + pyautogui.press(key) + except ImportError: + print("pyautogui not installed. Run: pip install pyautogui") + except Exception as e: + print(f"Error sending key '{key}': {e}") + + def swipe_left_tab(): + """Three-finger swipe left = switch to previous tab (Mac).""" + if OS == "Darwin": + os.system("""osascript -e 'tell application "System Events" to key code 123 using control down'""") # Left arrow + + def swipe_right_tab(): + """Three-finger swipe right = switch to next tab (Mac).""" + if OS == "Darwin": + os.system("""osascript -e 'tell application "System Events" to key code 124 using control down'""") # Right arrow + + + def start_presentation(): + """Start PowerPoint presentation (equivalent to pressing F5).""" + try: + pyautogui.press("f5") + print("šŸ“½ Started presentation") + except Exception as e: + print(f"āš ļø Error starting presentation: {e}") + + def next_slide(): + """Go to the next PowerPoint slide.""" + try: + pyautogui.press("right") + print("āž”ļø Next slide") + except Exception as e: + print(f"āš ļø Error moving to next slide: {e}") + + def previous_slide(): + """Go to the previous PowerPoint slide.""" + try: + pyautogui.press("left") + print("ā¬…ļø Previous slide") + except Exception as e: + print(f"āš ļø Error moving to previous slide: {e}") + + def exit_presentation(): + """Exits PowerPoint slideshow by bringing it to front and sending ESC.""" + try: + + + # Step 1: Bring PowerPoint to the foreground + os.system('osascript -e \'tell application "Microsoft PowerPoint" to activate\'') + time.sleep(0.5) # Let the window come to front + + # Step 2: Send ESC key to exit slideshow + pyautogui.press("esc") + print("šŸ›‘ Exited PowerPoint presentation") + + except Exception as e: + print(f"āš ļø Error exiting PowerPoint: {e}") + diff --git a/archive/collect_data.py b/src/archive/collect_data.py similarity index 100% rename from archive/collect_data.py rename to src/archive/collect_data.py diff --git a/gesture_cli_mapper.py b/src/archive/gesture_cli_mapper.py similarity index 92% rename from gesture_cli_mapper.py rename to src/archive/gesture_cli_mapper.py index 8a4d7ec..70e7ee4 100644 --- a/gesture_cli_mapper.py +++ b/src/archive/gesture_cli_mapper.py @@ -3,19 +3,22 @@ import inspect import actions -CONFIG_PATH = "gesture_config.json" + +CONFIG_PATH = os.getenv("GESTURAI_GESTURE_MAP") +DEFAULT_CONFIG_PATH = os.getenv("GESTURAI_GESTURE_MAP_DEFAULT") + # Load or create default mapping def load_mapping(): if os.path.exists(CONFIG_PATH): with open(CONFIG_PATH, "r") as f: return json.load(f) - return {"default": {}, "media_mode": {}, "presentation_mode": {}, "word_mode": {}} + def save_mapping(mapping): with open(CONFIG_PATH, "w") as f: json.dump(mapping, f, indent=2) - print("āœ… Mapping saved to gesture_config.json\n") + print("āœ… Mapping saved\n") def list_modes(mapping): print("\nAvailable modes:") diff --git a/gesture_utils.py b/src/archive/gesture_utils.py similarity index 100% rename from gesture_utils.py rename to src/archive/gesture_utils.py diff --git a/hand_tracker.py b/src/archive/hand_tracker.py similarity index 96% rename from hand_tracker.py rename to src/archive/hand_tracker.py index a789958..8da9c5f 100644 --- a/hand_tracker.py +++ b/src/archive/hand_tracker.py @@ -1,7 +1,12 @@ import cv2 # type: ignore import mediapipe as mp # type: ignore +import numpy as np + + + class HandTracker: + def __init__(self, detection_conf=0.5, tracking_conf=0.5): self.mp_hands = mp.solutions.hands self.hands = self.mp_hands.Hands(min_detection_confidence=detection_conf, diff --git a/archive/main.py b/src/archive/main.py similarity index 92% rename from archive/main.py rename to src/archive/main.py index d5f1495..61e1e72 100644 --- a/archive/main.py +++ b/src/archive/main.py @@ -1,7 +1,7 @@ import cv2 import time -from hand_tracker import HandTracker -from gesture_utils import detect_gesture # central detection logic +from archive.hand_tracker import HandTracker +from archive.gesture_utils import detect_gesture # central detection logic from actions import gesture_action_map # maps gestures to functions # Initialize HandTracker diff --git a/archive/test_actions.py b/src/archive/test_actions.py similarity index 100% rename from archive/test_actions.py rename to src/archive/test_actions.py diff --git a/archive/test_pause.py b/src/archive/test_pause.py similarity index 100% rename from archive/test_pause.py rename to src/archive/test_pause.py diff --git a/src/crud.py b/src/crud.py new file mode 100644 index 0000000..fe80d8e --- /dev/null +++ b/src/crud.py @@ -0,0 +1,458 @@ +import json +import os +import src.gesture_data as gd +import src.gesture_model as gm +import pandas as pd +import torch + +# SUPPORT FUNCTIONS - +# TODO consider removing these and using a library like `jsonschema` for validation + +def save_json_mapping(path, mapping): + try: + with open(path, "w") as f: + json.dump(mapping, f, indent=2) + except Exception as e: + print(f"Error saving file: {e}") + return False + # cleanup - close file if it was opened + finally: + try: + f.close() + except NameError: + pass + except Exception as e: + print(f"Error closing file: {e}") + +def load_json_mapping(path): + try: + with open(path, "r") as f: + mapping = json.load(f) + f.close() + return mapping + except FileNotFoundError: + print(f"File not found: {path}") + return {} + except json.JSONDecodeError: + print(f"Error decoding JSON from file: {path}") + return {} + except Exception as e: + print(f"Unexpected error: {e}") + return {} + # cleanup - close file if it was opened + finally: + f.close() + +def load_gesture_data( + data_path, + gesture_name, + suffix = ".csv"): + """ + Load training data from a CSV file. + + Args: + data_path (str): Path to the CSV file containing gesture data. + + Returns: + pd.DataFrame: DataFrame containing the gesture data. + """ + file_path = os.path.join(data_path, gesture_name + suffix) + try: + gesture_data = pd.read_csv(file_path) + # add a column 'gesture_name' to the data + gesture_data['gesture_name'] = gesture_name + return gesture_data + except FileNotFoundError: + print(f"File not found: {file_path}") + return pd.DataFrame() + except pd.errors.EmptyDataError: + print(f"Empty CSV file: {file_path}") + return pd.DataFrame() + except Exception as e: + print(f"Unexpected error: {e}") + return pd.DataFrame() + + +# CONTEXT CRUD OPERATIONS + +def create_context( + context_name, + gesture_action_map_path): + """ + Add a new context/mode to the gesture map. + + Args: + context_name (str): Name of the new context to add + gesture_map (dict): The current gesture action map + + Returns: + bool: True if successful, False if the context already exists or if the name is invalid + """ + if context_name[:5] != "mode_": + print(f"Context name '{context_name}' must start with 'mode_'.") + return False + + # Load current gesture-action map + gesture_action_map = load_json_mapping(gesture_action_map_path) + + if context_name in gesture_action_map: + return False + + # Add empty context to the map + gesture_action_map[context_name] = {} + + # Save the updated map + save_json_mapping(gesture_action_map_path, gesture_action_map) + return True + + +def delete_context( + context_name, + gesture_action_map_path): + """ + Remove a context/mode from the gesture map. + + Args: + context_name (str): Name of the context to remove + gesture_map (dict): The current gesture action map + + Returns: + bool: True if successful, False if the context doesn't exist or is protected + """ + # Load current gesture-action map + gesture_action_map = load_json_mapping(gesture_action_map_path) + + # Protect essential contexts from being removed + protected_contexts = ["mode_context_selection", "mode_default"] + + if context_name not in gesture_action_map: + return False + + if context_name in protected_contexts: + return False + + # Remove the context + del gesture_action_map[context_name] + + # Also remove references to this context from mode_context_selection + if "mode_context_selection" in gesture_action_map: + context_selection = gesture_action_map["mode_context_selection"] + # Find and remove any gesture that points to the removed context + for gesture, action in list(context_selection.items()): + if action == context_name: + del context_selection[gesture] + + # Save the updated map + save_json_mapping(gesture_action_map_path, gesture_action_map) + return True + +def rename_context( + current_context_name, + new_context_name, + gesture_action_map_path): + """ + Rename a context/mode in the gesture map. + + Args: + current_context_name (str): Current name of the context + new_context_name (str): New name for the context + gesture_map (dict): The current gesture action map + + Returns: + bool: True if successful, False if the context doesn't exist, is protected, + or the new name already exists + """ + # Load current gesture-action map + gesture_action_map = load_json_mapping(gesture_action_map_path) + + # Protect essential contexts from being renamed + protected_contexts = ["mode_context_selection"] + if current_context_name in protected_contexts: + print(f"Cannot rename protected context: {current_context_name}") + return False + + if current_context_name not in gesture_action_map.keys(): + print(f"Context '{current_context_name}' does not exist.") + return False + if new_context_name in gesture_action_map.keys(): + print(f"Context '{new_context_name}' already exists.") + return False + + # Create new entry with the same mappings + gesture_action_map[new_context_name] = gesture_action_map[current_context_name] + + # Remove the old entry + del gesture_action_map[current_context_name] + + # Update references in mode_context_selection + if "mode_context_selection" in gesture_action_map: + context_selection = gesture_action_map["mode_context_selection"] + # Find and update any gesture that points to the renamed context + for gesture, action in list(context_selection.items()): + if action == current_context_name: + context_selection[gesture] = new_context_name + + # Save the updated map + save_json_mapping(gesture_action_map_path, gesture_action_map) + return True + + + +# GESTURE-ACTION CRUD OPERATIONS + +def create_gesture_action_mapping( + gesture_name, + action_name, + context_name, + gesture_action_map_path): + + gesture_action_map = load_json_mapping(gesture_action_map_path) + + # Check if the context exists + if context_name not in gesture_action_map: + print(f"Context '{context_name}' does not exist.") + return False + + # Check if the gesture already exists in the context + if gesture_name in gesture_action_map[context_name]: + print(f"Gesture '{gesture_name}' already exists in context '{context_name}'.") + return False + + # Check if the action already exists in the context + if action_name in gesture_action_map[context_name].values(): + print(f"Action '{action_name}' already exists in context '{context_name}'.") + return False + + # Add the new gesture-action mapping to the context + gesture_action_map[context_name][gesture_name] = action_name + + # Save the updated gesture-action map + save_json_mapping(gesture_action_map_path, gesture_action_map) + return True + +def delete_gesture_action_mapping( + gesture_name, + action_name, + context_name, + gesture_action_map_path): + + gesture_action_map = load_json_mapping(gesture_action_map_path) + + # Check if the context exists + if context_name not in gesture_action_map: + print(f"Context '{context_name}' does not exist.") + return False + + # Check if the gesture exists in the context + if gesture_name not in gesture_action_map[context_name]: + print(f"Gesture '{gesture_name}' does not exist in context '{context_name}'.") + return False + + # Check if the gesture-action mapping exists + if gesture_action_map[context_name][gesture_name] != action_name: + print(f"Action '{action_name}' does not exist for gesture '{gesture_name}' in context '{context_name}'.") + return False + + # Remove the gesture-action mapping from the context + del gesture_action_map[context_name][gesture_name] + + # Save the updated gesture-action map + save_json_mapping(gesture_action_map_path, gesture_action_map) + return True + + +# GESTURE CRUD OPERATIONS + +def create_gesture( + created_gesture_name, + gesture_index_map_path, + gesture_data_path, + gesture_model_path): + + # LOAD GESTURE INDEX MAP AND ADD NEW GESTURE-INDEX ITEM + gesture_index_map = load_json_mapping(gesture_index_map_path) + gesture_index_map[created_gesture_name] = len(gesture_index_map) + + # LOAD EXISTING GESTURE DATA + training_dfs = [] + + for gesture_name in gesture_index_map.keys(): + # Load the gesture data and add a column for the gesture name + if gesture_name != created_gesture_name: + gesture_data = load_gesture_data( + gesture_data_path, + gesture_name, + ".csv") + training_dfs.append(gesture_data) + + # GATHER NEW GESTURE DATA + new_data = gd.gather_gesture_data(created_gesture_name) + training_dfs.append(new_data) + + # CONCATENATE ALL TRAINING DATA + training_data = pd.concat(training_dfs, ignore_index=True) + + # TRAIN NEW MODEL + model = gm.model_training_pipeline( + training_data, + gesture_index_map) + + # SAVE UPDATED MAPS AND MODEL + # TODO LATER: Add a check to see if the model training was successful; if not, revert + # TODO LATER: Make this an atomic operation - if any part fails, revert all changes + + # Save the new gesture-index map, overwriting the old index map + save_json_mapping(gesture_index_map_path, gesture_index_map) + + # Save the data for the new gesture + new_data = new_data.drop(columns=['gesture_name']) + new_data.to_csv(gesture_data_path + created_gesture_name + ".csv", index=False) + + #Save the new model, overwriting the old model + torch.save(model, gesture_model_path) + + return True + + + + +# Add function to alter a gesture - capturing new data +# and retraining the gesture recognition model without altering +# the gesture-action map +def retrain_gesture( + retrained_gesture_name, + gesture_index_map_path, + gesture_data_path, + gesture_model_path): + + # LOAD GESTURE INDEX MAP (READ-ONLY) + gesture_index_map = load_json_mapping(gesture_index_map_path) + + # LOAD TRAINING DATA, REPLACING OLD GESTURE DATA WITH NEW GESTURE DATA + training_dfs = [] + + for gesture_name in gesture_index_map.keys(): + if gesture_name != retrained_gesture_name: + # Load the gesture data and add a column for the gesture name + gesture_data = load_gesture_data( + gesture_data_path, + gesture_name, + ".csv") + training_dfs.append(gesture_data) + else: + # GATHER NEW GESTURE DATA + new_gesture_data = gd.gather_gesture_data(retrained_gesture_name) + training_dfs.append(new_gesture_data) + + # CONCATENATE ALL TRAINING DATA + training_data = pd.concat(training_dfs, ignore_index=True) + + # TRAIN NEW MODEL + model = gm.model_training_pipeline(training_data, gesture_index_map) + + # SAVE NEW DATA AND MODEL + # TODO LATER make this an atomic operation - if any part fails, revert all changes + # replace old gesture data with new gesture data + new_gesture_data = new_gesture_data.drop(columns=['gesture_name']) + new_gesture_data.to_csv(gesture_data_path + "/" + retrained_gesture_name + ".csv", index=False) + + #Save the new model, overwriting the old model + torch.save(model, gesture_model_path) + + return True + +# TODO problem - doesn't rename the gesture within the data file - but this is extraneous +# TODO refactor project to exclude score, capture_number, and gesture_name from the data file +def rename_gesture( + current_gesture_name, + new_gesture_name, + gesture_index_map_path, + gesture_action_map_path, + gesture_data_path): + # CREATE NEW MAPS + # Update the gesture name in the gesture-index map + gesture_index_map = load_json_mapping(gesture_index_map_path) + gesture_index_map[new_gesture_name] = gesture_index_map[current_gesture_name] + del gesture_index_map[current_gesture_name] + + # Update the gesture name in each context of the gesture-action map + gesture_action_map = load_json_mapping(gesture_action_map_path) + for context in gesture_action_map.keys(): + if current_gesture_name in gesture_action_map[context]: + gesture_action_map[context][new_gesture_name] = gesture_action_map[context][current_gesture_name] + del gesture_action_map[context][current_gesture_name] + + # SAVE NEW MAPS & UPDATE GESTURE DATA FILE NAME + # TODO LATER make this an atomic operation - if any part fails, revert all changes + save_json_mapping(gesture_index_map_path, gesture_index_map) + save_json_mapping(gesture_action_map_path, gesture_action_map) + os.rename(gesture_data_path + "/" + current_gesture_name + ".csv", gesture_data_path + "/" + new_gesture_name + ".csv") + return True + + + +def delete_gesture( + deleted_gesture_name, + gesture_index_map_path, + gesture_action_map_path, + gesture_data_path, + gesture_model_path): + + # LOAD AND UPDATE MAPS TO EXCLUDE TARGET GESTURE + gesture_index_map = load_json_mapping(gesture_index_map_path) + # Remove the gesture from the index map + del gesture_index_map[deleted_gesture_name] + # Renumber the indices of the remaining gestures + i = 0 + new_gesture_index_map = {} + for k in gesture_index_map.keys(): + new_gesture_index_map[k] = i + i += 1 + gesture_index_map = new_gesture_index_map + + print(f"Gesture index map: {gesture_index_map}") + + # Remove the gesture from each context of the gesture-action map + gesture_action_map = load_json_mapping(gesture_action_map_path) + for v in gesture_action_map.values(): + if deleted_gesture_name in v.keys(): + del v[deleted_gesture_name] + + print (f"Gesture action map: {gesture_action_map}") + + # LOAD TRAINING DATA - EXCLUDES TARGET GESTURE DATA + training_dfs = [] + + for gesture_name in gesture_index_map.keys(): + # Load the gesture data and add a column for the gesture name + gesture_data = load_gesture_data( + gesture_data_path, + gesture_name, + ".csv") + training_dfs.append(gesture_data) + + # CONCATENATE ALL TRAINING DATA + training_data = pd.concat(training_dfs, ignore_index=True) + + print(f"Training data: {training_data}") + print(f"Training data shape: {training_data.shape}") + + # TRAIN NEW MODEL + model = gm.model_training_pipeline( + training_data, + gesture_index_map) + + # SAVE MAPS AND MODEL; DELETE OLD DATA + # TODO LATER: Add a check to see if the model training was successful; if not, revert + # TODO LATER: Make this an atomic operation - if any part fails, revert all changes + + # Save the new mappigns, overwriting the old mappings + save_json_mapping(gesture_index_map_path, gesture_index_map) + save_json_mapping(gesture_action_map_path, gesture_action_map) + + #Save the new model, overwriting the old model + torch.save(model, gesture_model_path) + + #Delete the old gesture data file + os.remove(gesture_data_path + "/" + deleted_gesture_name + ".csv") + return True \ No newline at end of file diff --git a/src/gesture_data.py b/src/gesture_data.py new file mode 100644 index 0000000..55318b9 --- /dev/null +++ b/src/gesture_data.py @@ -0,0 +1,137 @@ +import cv2 +import mediapipe as mp +import pandas as pd + + + +def gather_gesture_data(gesture_name): + + # Initialize MediaPipe Hands + mp_hands = mp.solutions.hands + mp_drawing = mp.solutions.drawing_utils + mp_drawing_styles = mp.solutions.drawing_styles + + # Configure MediaPipe Hands with default settings + hands = mp_hands.Hands( + static_image_mode=False, + max_num_hands=1, + min_detection_confidence=0.5, + min_tracking_confidence=0.5 + ) + num_landmarks = 21 + + # Initialize the webcam (0 is usually the default camera) + cap = cv2.VideoCapture(0) + + # Set camera resolution to HD (1280x720) for better quality + cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280) + cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720) + + print("Press 'c' to capture current landmarks") + print ("Press 'r' reset captured landmarks") + print("Press 's' to save the captured landmarks") + + # Data collection application + capture_number = 0 + + # Create landmarks header + landmarks_header = [ + 'handedness'] + for landmark_id in range(num_landmarks): + for point_id in ['x', 'y', 'z']: + landmarks_header.append(f'{landmark_id}_{point_id}') + + landmarks_df = pd.DataFrame(columns=landmarks_header) + + # Main loop to process video frames and capture landmarks + while cap.isOpened(): + # Read frame from webcam + success, frame = cap.read() + if not success: + print("Failed to read from webcam") + break + + # Flip the frame horizontally for a more intuitive mirror view + frame = cv2.flip(frame, 1) + + # Convert BGR image to RGB (CV2 uses BGR but MediaPipe requires RGB) + rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) + + # Process the frame with MediaPipe Hands + landmarks = hands.process(rgb_frame) + + # Create a copy of the frame to draw on + display_frame = frame.copy() + + + # Draw hand landmarks if detected + if landmarks.multi_hand_landmarks: + for hand_landmarks in landmarks.multi_hand_landmarks: + mp_drawing.draw_landmarks( + display_frame, + hand_landmarks, + mp_hands.HAND_CONNECTIONS, + mp_drawing_styles.get_default_hand_landmarks_style(), + mp_drawing_styles.get_default_hand_connections_style() + ) + + cv2.putText( + display_frame, + f'Capturing {gesture_name} #{capture_number}', + (10, 30), + cv2.FONT_HERSHEY_SIMPLEX, + 0.7, + (255, 255, 255), + 2) + + cv2.imshow("MediaPipe Hands Capture", display_frame) + + + # Handle keyboard input + # masking to capture only the lower 8 bits to help with cross-platform compatibility + key = cv2.waitKey(1) & 0xFF + + # 'c' key to capture current frame and landmarks + # TODO add a check to see if all landmarks are present - don't capture bad data + if key == ord('c'): + if landmarks.multi_hand_world_landmarks: + + current_item = { + 'handedness': landmarks.multi_handedness[0].classification[0].label + } + for landmark_id in range(num_landmarks): + landmark = landmarks.multi_hand_landmarks[0].landmark[landmark_id] + current_item[f'{landmark_id}_x'] = landmark.x + current_item[f'{landmark_id}_y'] = landmark.y + current_item[f'{landmark_id}_z'] = landmark.z + + # Append landmarks data to dataframe + landmarks_df = pd.concat([landmarks_df, pd.DataFrame([current_item])], ignore_index=True) + + capture_number += 1 + print("Frame captured with hand landmarks") + else: + print("No hands detected. Position your hand in the frame.") + + elif key == ord('r'): + # Reset captured landmarks + landmarks_df = pd.DataFrame(columns=landmarks_header) + capture_number = 0 + print("Reset captured landmarks") + + # 's' key to stop and return captured landmarks + elif key == ord('s'): + + landmarks_df['gesture_name'] = gesture_name + + # Release resources + cap.release() + cv2.destroyAllWindows() + hands.close() + + # Return the captured landmarks DataFrame + return landmarks_df + + + + \ No newline at end of file diff --git a/src/gesture_model.py b/src/gesture_model.py new file mode 100644 index 0000000..9da6c1c --- /dev/null +++ b/src/gesture_model.py @@ -0,0 +1,228 @@ +import torch.nn as nn +import numpy as np +import numpy as np +import torch +import torch.nn as nn +import torch.optim as optim +from sklearn.model_selection import train_test_split +from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay +import matplotlib.pyplot as plt +import pandas as pd +import mediapipe as mp +import src.gesture_model as gm + +# TODO add dropout layers to the model to prevent overfitting +# TODO add batch normalization to the model to improve training speed and stability +# TODO turn this into a simple sequential model to simplify the code? +# TODO switch to leaky relu? +class GestureClassifier(nn.Module): + def __init__(self, input_features, output_classes): + super(GestureClassifier, self).__init__() + self.fc1 = nn.Linear(input_features, 256) + self.fc2 = nn.Linear(256, 64) + self.fc3 = nn.Linear(64, output_classes) + self.relu = nn.ReLU() + + def forward(self, x): + x = self.relu(self.fc1(x)) + x = self.relu(self.fc2(x)) + x = self.fc3(x) + return x + + +def model_training_pipeline( + df : pd.DataFrame, + gesture_index_map : dict, + sample_size_per_gesture : int = 100, + sample_size_other_gesture : int = 250): + + # Drop rows with NaN values + df = df.dropna() + + # Convert handedness to numeric values + df['handedness'] = df['handedness'].map({'Left': -1, 'Right': 1}) + + # Convert gesture labels to numeric values + df['y'] = df['gesture_name'].map(gesture_index_map) + df = df.drop(columns=['gesture_name']) + + # Balance the sample + df = gm.get_balanced_sample( + df, + sample_size_per_gesture = sample_size_per_gesture, + sample_size_other_gesture = sample_size_other_gesture + ) + + # Normalize the landmarks + df = normalize_landmarks_df(df) + + # X,y split + X = df.drop(columns=["y"]) + y = df["y"] + + # Train and return the model + return train_model(X,y) + + +def normalize_landmarks(hand_landmarks): + """ + Args: + hand_landmarks: List of landmarks, each landmark is a list of [x, y, z] coordinates. + + Returns: + List of lists of normalized landmarks, where each landmark is a list of [x, y, z] coordinates. + """ + + # Get the average landmark coordinates and center the hand coordinates + hand_landmarks_centers = [] + for dim in range(3): + hand_landmarks_centers.append(np.mean([landmark[dim] for landmark in hand_landmarks])) + + for lm_id in range(len(hand_landmarks)): + for dim in range(3): + hand_landmarks[lm_id][dim] -= hand_landmarks_centers[dim] + + # Get center, min and max for each dimension + hand_landmarks_centers = [] + hand_landmarks_mins = [] + hand_landmarks_maxs = [] + for dim in range(3): + hand_landmarks_centers.append(np.mean([landmark[dim] for landmark in hand_landmarks])) + hand_landmarks_mins.append(np.min([landmark[dim] for landmark in hand_landmarks])) + hand_landmarks_maxs.append(np.max([landmark[dim] for landmark in hand_landmarks])) + + # Then, scale them to fit within the range of -1 to 1 + for lm_id in range(len(hand_landmarks)): + for dim in range(3): + # First, center the landmarks around the mean + hand_landmarks[lm_id][dim] -= hand_landmarks_centers[dim] + # Then, scale them to fit within the range of -1 to 1 + # based on the distance of the max and min values from the mean + denom = max(abs(hand_landmarks_maxs[dim]-hand_landmarks_centers[dim]), + abs(hand_landmarks_mins[dim]-hand_landmarks_centers[dim])) + if denom > 0: + hand_landmarks[lm_id][dim] /= denom + else: + hand_landmarks[lm_id][dim] = 0 + + return hand_landmarks + + +def get_balanced_sample( + df : pd.DataFrame, + sample_size_per_gesture : int = 100, + sample_size_other_gesture : int = 250): + + # Create an empty dataframe to store selected samples + df_balanced = pd.DataFrame(columns=df.columns) + + # For each handedness and gesture, select observations and add to df_sampled + for handedness in [-1, 1]: + for gesture in df['y'].unique(): + sample_size = sample_size_other_gesture if gesture == 'other_gesture' else sample_size_per_gesture + df_temp = df[(df['handedness'] == handedness) & (df['y'] == gesture)] + + # Check if we have enough samples + if len(df_temp) >= sample_size: + subsample = df_temp.sample(n=sample_size, random_state=42) + df_balanced = pd.concat([df_balanced, subsample], ignore_index=True) + else: + print(f"Not enough samples for gesture {gesture} with handedness = {handedness}.") + return None + + df_balanced = df_balanced.reset_index(drop=True) + + + return df_balanced + +# Wrapper function to normalize each set of landmarks in a dataframe +# using the normalize_landmarks function +def normalize_landmarks_df(df): + + df = df.copy() + + # For each row of the dataframe, normalize the landmarks + for index, row in df.iterrows(): + # Extract landmarks from the row + hand_landmarks = [] + for i in range(21): + hand_landmarks.append([row[f'{i}_x'], row[f'{i}_y'], row[f'{i}_z']]) + + # Normalize the landmarks + normalized_landmarks = normalize_landmarks(hand_landmarks) + + # Update the dataframe with normalized landmarks + for i in range(21): + df.at[index, f'{i}_x'] = normalized_landmarks[i][0] + df.at[index, f'{i}_y'] = normalized_landmarks[i][1] + df.at[index, f'{i}_z'] = normalized_landmarks[i][2] + + return df + + +# Takes a dataframe with columns ['x', 'y', 'z'] for each landmark +# A numeric column 'handedness' indicating the handedness of the gesture (1 for right, -1 for left) +# and a numeric label column 'y' +# Returns a newly trained model +def train_model(X: pd.DataFrame, y: pd.DataFrame): + + # Split data (stratified ensures class balance in both sets) + X_train, X_test, y_train, y_test = train_test_split( + X, y, test_size=0.2, random_state=42, stratify=y + ) + + # Initialize model + input_size = X.shape[1] + num_classes = len(set(y)) + model = GestureClassifier(input_size, num_classes) + + # Training config + criterion = nn.CrossEntropyLoss() + optimizer = optim.Adam(model.parameters(), lr=0.002) + epochs = 30 + num_classes * 3 + + # Convert to tensors + X_train_tensor = torch.tensor(X_train.values.astype(np.float32), dtype=torch.float32) + y_train_tensor = torch.tensor(y_train.values.astype(np.int64), dtype=torch.int64) + X_test_tensor = torch.tensor(X_test.values.astype(np.float32), dtype=torch.float32) + y_test_tensor = torch.tensor(y_test.values.astype(np.int64), dtype=torch.int64) + + # Train model + + for epoch in range(epochs): + model.train() + optimizer.zero_grad() + outputs = model(X_train_tensor) + loss = criterion(outputs, y_train_tensor) + loss.backward() + optimizer.step() + print(f"Epoch {epoch+1}/{epochs}, Training Loss: {loss.item():.4f}") + + + # Evaluate on test set + model.eval() + with torch.no_grad(): + test_outputs = model(X_test_tensor) + predicted = torch.argmax(test_outputs, dim=1) + accuracy = (predicted == y_test_tensor).sum().item() / len(y_test_tensor) + print(f"\nāœ… Test Accuracy: {accuracy * 100:.2f}%") + + # # Confusion matrix + # cm = confusion_matrix(y_test, predicted) + # disp = ConfusionMatrixDisplay(confusion_matrix=cm) + # disp.plot(cmap="Blues") + # plt.title("Confusion Matrix") + # plt.xlabel("Predicted") + # plt.ylabel("True") + # plt.show() + + + return model + + + + + + + + diff --git a/training.py b/training.py deleted file mode 100644 index a288771..0000000 --- a/training.py +++ /dev/null @@ -1,102 +0,0 @@ -import pickle -import numpy as np -import torch -import torch.nn as nn -import torch.optim as optim -from sklearn.model_selection import train_test_split -from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay -import matplotlib.pyplot as plt - -# Load dataset -with open("gesture_data.pkl", "rb") as f: - dataset = pickle.load(f) - -X = np.array([item[0] for item in dataset]) # Normalized keypoints -y = np.array([item[1] for item in dataset]) # Gesture labels - -# Split data (stratified ensures class balance in both sets) -X_train, X_test, y_train, y_test = train_test_split( - X, y, test_size=0.2, random_state=42, stratify=y -) - -# Define model architecture -class GestureClassifier(nn.Module): - def __init__(self, input_size, num_classes): - super(GestureClassifier, self).__init__() - self.fc1 = nn.Linear(input_size, 128) - self.fc2 = nn.Linear(128, 64) - self.fc3 = nn.Linear(64, num_classes) - self.relu = nn.ReLU() - - def forward(self, x): - x = self.relu(self.fc1(x)) - x = self.relu(self.fc2(x)) - x = self.fc3(x) - return x - -# Initialize model -input_size = X.shape[1] -num_classes = len(set(y)) -model = GestureClassifier(input_size, num_classes) - -# Training config -criterion = nn.CrossEntropyLoss() -optimizer = optim.Adam(model.parameters(), lr=0.001) -epochs = 65 - -# Convert to tensors -X_train_tensor = torch.tensor(X_train, dtype=torch.float32) -y_train_tensor = torch.tensor(y_train, dtype=torch.long) -X_test_tensor = torch.tensor(X_test, dtype=torch.float32) -y_test_tensor = torch.tensor(y_test, dtype=torch.long) - -# Train model -model.train() -for epoch in range(epochs): - optimizer.zero_grad() - outputs = model(X_train_tensor) - loss = criterion(outputs, y_train_tensor) - loss.backward() - optimizer.step() - print(f"Epoch {epoch+1}/{epochs}, Loss: {loss.item():.4f}") - -# Evaluate on test set -model.eval() -with torch.no_grad(): - test_outputs = model(X_test_tensor) - predicted = torch.argmax(test_outputs, dim=1) - accuracy = (predicted == y_test_tensor).sum().item() / len(y_test_tensor) - print(f"\nāœ… Test Accuracy: {accuracy * 100:.2f}%") - - # Confusion matrix - cm = confusion_matrix(y_test, predicted) - disp = ConfusionMatrixDisplay(confusion_matrix=cm) - disp.plot(cmap="Blues") - plt.title("Confusion Matrix") - plt.xlabel("Predicted") - plt.ylabel("True") - plt.show() - -# Save model -torch.save(model.state_dict(), "gesture_model.pth") -print("šŸŽ‰ Model saved to gesture_model.pth") - -# Save label map -GESTURE_LABELS = { - 'open_palm': 0, - 'fist': 1, - 'peace_sign': 2, - 'thumbs_up': 3, - 'pointing_finger': 4, - 'ok_sign': 5, - 'thumbs_down': 6, - 'three_fingers': 7, - 'rock_on': 8, - 'pinch': 9, - 'swipe_left': 10, - 'swipe_right': 11 -} -label_map = {v: k for k, v in GESTURE_LABELS.items()} -with open("label_map.pkl", "wb") as f: - pickle.dump(label_map, f) -print("šŸ“Œ Label map saved to label_map.pkl")