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Set default APP_DIR path #32

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Set default APP_DIR path #32

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54 changes: 27 additions & 27 deletions main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@
load_dotenv()
dotenv_file = dotenv.find_dotenv()

logfile = os.getenv("APP_DIR") + '/sleepy_logs.log'
logfile = os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/sleepy_logs.log'
logging.basicConfig(filename=logfile,
filemode='a+',
format='%(asctime)s,%(msecs)d %(name)s %(levelname)s %(message)s',
Expand All @@ -64,7 +64,7 @@
focus_bounding_box = (None, None, None, None)
classifier_resolution = 256

with open(os.getenv("APP_DIR") + '/user_defined_crop_area.txt', 'r', encoding="utf-8") as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/user_defined_crop_area.txt', 'r', encoding="utf-8") as f:
crop_area = f.read()
focusRegionArr = crop_area.split(',')
print('reading focusRegionArr: ', focusRegionArr)
Expand All @@ -81,7 +81,7 @@
lock_model_use = False
creepy_baby_model = None
try:
with open(os.getenv("APP_DIR") + '/blanket_model/creepy_baby_model.pkl', 'rb') as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/creepy_baby_model.pkl', 'rb') as f:
creepy_baby_model = pickle.load(f)
except Exception as e:
print("No blanket model found at startup: ", e)
Expand Down Expand Up @@ -273,7 +273,7 @@ def process_baby_image_models(self, img, debug_img):
@debounce(180)
def write_wakeness_event(self, wake_status, img):
str_timestamp = str(int(time.time()))
sleep_data_base_path = os.getenv("APP_DIR")
sleep_data_base_path = os.getenv("APP_DIR", "/usr/app/babysleepcoach")
p = sleep_data_base_path + '/' + str_timestamp + '.png'
if wake_status: # woke up
log_string = "1," + str_timestamp + "\n"
Expand All @@ -287,7 +287,7 @@ def write_wakeness_event(self, wake_status, img):
# now = datetime.datetime.now()
# now_time = now.time()
# notifications_enabled = False
# with open(os.getenv("APP_DIR") + '/notifications.txt', 'r', encoding="utf-8") as f:
# with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/notifications.txt', 'r', encoding="utf-8") as f:
# notifications_enabled_text = f.read()
# notifications_enabled = notifications_enabled_text == 'true'
# if notifications_enabled and now_time >= datetime.time(7,00) or now_time <= datetime.time(22,00): # day time
Expand Down Expand Up @@ -460,14 +460,14 @@ def blanket_logic(self, image, body_found, raw_uncropped_image):
proba_string = str(y[0][0]) + ',' + str(y[0][1]) + ',' + str(time.time())
model_proba = proba_string

# with open(os.getenv("APP_DIR") + '/blanket_model/current_output/proba.txt', 'w', encoding="utf-8") as f:
# with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/current_output/proba.txt', 'w', encoding="utf-8") as f:
# f.write(proba_string)
# cv2.imwrite(os.getenv("APP_DIR") + '/blanket_model/current_output/raw.png', image)
# cv2.imwrite(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/current_output/raw.png', image)
except Exception as e:
model_sees_baby = None
print("Something went wrong while invoking creepy blanket model: ", e)

cv2.imwrite(os.getenv("APP_DIR") + '/blanket_model/current_output/raw_uncropped.png', raw_uncropped_image)
cv2.imwrite(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/current_output/raw_uncropped.png', raw_uncropped_image)


def frame_logic(self, raw_img, raw_uncropped_image, debug_frame_q):
Expand Down Expand Up @@ -522,10 +522,10 @@ def frame_logic(self, raw_img, raw_uncropped_image, debug_frame_q):
# This basically does the same thing as the live version, but is very useful for testing
def recorded(self, debug_frame_q, cropped_raw_frame_q):
# cap = cv2.VideoCapture(os.getenv("VIDEO_PATH"))
cap = cv2.VideoCapture(os.getenv("APP_DIR") + '/videos/baby-011013-011040.mp4')
# cap = cv2.VideoCapture(os.getenv("APP_DIR") + '/raw_data/babywaking.mp4')
# cap = cv2.VideoCapture(os.getenv("APP_DIR") + '/raw_data/baby_eyes.mp4')
# cap = cv2.VideoCapture(os.getenv("APP_DIR") + '/raw_data/falling_asleep_eyes.mp4')
cap = cv2.VideoCapture(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/videos/baby-011013-011040.mp4')
# cap = cv2.VideoCapture(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/raw_data/babywaking.mp4')
# cap = cv2.VideoCapture(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/raw_data/baby_eyes.mp4')
# cap = cv2.VideoCapture(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/raw_data/falling_asleep_eyes.mp4')

global focus_bounding_box
global classifier_resolution
Expand Down Expand Up @@ -806,15 +806,15 @@ def getResultAndReasons():
@cross_origin()
def getSleepNotificationsEnabled():
notifications_enabled = None
with open(os.getenv("APP_DIR") + '/notifications.txt', 'r', encoding="utf-8") as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/notifications.txt', 'r', encoding="utf-8") as f:
notifications_enabled = f.read()
return notifications_enabled

@app.route('/setSleepNotificationsEnabled/<enabled>')
@cross_origin()
def setSleepNotificationsEnabled(enabled):
print('enabled? ', enabled)
with open(os.getenv("APP_DIR") + '/notifications.txt', 'w', encoding="utf-8") as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/notifications.txt', 'w', encoding="utf-8") as f:
f.write(enabled)
return 'ok'

Expand Down Expand Up @@ -858,12 +858,12 @@ def setAIFocusRegion(focusRegion):

if focusRegion == 'reset':
print("RESET")
with open(os.getenv("APP_DIR") + '/user_defined_crop_area.txt', 'w', encoding="utf-8") as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/user_defined_crop_area.txt', 'w', encoding="utf-8") as f:
f.write(',,,')
focus_bounding_box = (None, None, None, None)
return 'reset ok'

with open(os.getenv("APP_DIR") + '/user_defined_crop_area.txt', 'w', encoding="utf-8") as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/user_defined_crop_area.txt', 'w', encoding="utf-8") as f:
f.write(focusRegion)

print('focusRegion: ', focusRegion)
Expand All @@ -887,7 +887,7 @@ def setAIFocusRegion(focusRegion):
master_image_data_dict = {"baby": [], "no_baby": []}
# large retrain w/ all the raw images, using newly set bounds
# so user doesnt have to restart/recollect from scratch, if updating
input_location = os.getenv("APP_DIR") + '/blanket_model/input'
input_location = os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/input'
input_paths = os.listdir(input_location)
for path in input_paths:
all_inputs = os.listdir(f"{input_location}/{path}")
Expand All @@ -907,7 +907,7 @@ def setAIFocusRegion(focusRegion):
master_image_data_dict[path].append(cropped_resized_blurred_image_data.flatten().tolist())
cv2.imwrite(f'./tmp/{input}', cropped_resized_blurred_image_data)

with open(os.getenv("APP_DIR") + "/blanket_model/output/image_data.json", "w") as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + "/blanket_model/output/image_data.json", "w") as f:
json.dump(master_image_data_dict, f)

# flatten image data for storage
Expand All @@ -919,10 +919,10 @@ def setAIFocusRegion(focusRegion):
final_clf = svm.SVC(probability=True, C=0.1, gamma=0.0001, kernel='poly')
final_clf.fit(all_images_flat, all_labels)

with open(os.getenv("APP_DIR") + '/blanket_model/creepy_baby_model.pkl','wb') as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/creepy_baby_model.pkl','wb') as f:
pickle.dump(final_clf,f)

with open(os.getenv("APP_DIR") + '/blanket_model/creepy_baby_model.pkl', 'rb') as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/creepy_baby_model.pkl', 'rb') as f:
creepy_baby_model = pickle.load(f)

lock_model_use = False
Expand All @@ -941,25 +941,25 @@ def retrainWithNewSample(classification):
global classifier_resolution
print("\n\n" + classification + "\n\n")

new_input_location = os.getenv("APP_DIR") + '/blanket_model/input/' + classification + '/' + classification + '_' + str(int(time.time())) + '.png'
new_input_location = os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/input/' + classification + '/' + classification + '_' + str(int(time.time())) + '.png'
# move image indicated by user from current_output dir to input dir
shutil.move(os.getenv("APP_DIR") + "/blanket_model/current_output/raw_uncropped.png", new_input_location)
shutil.move(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + "/blanket_model/current_output/raw_uncropped.png", new_input_location)

# read it, move to np
image = Image.open(new_input_location)
image_data = np.asarray(image)

# open & insert into image_data.json, save it off
all_images_dict = {}
with open(os.getenv("APP_DIR") + '/blanket_model/output/image_data.json', "r") as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/output/image_data.json', "r") as f:
all_images_dict = json.load(f)

cropped_image_data = image_data[focus_bounding_box[1]:focus_bounding_box[1]+focus_bounding_box[3], focus_bounding_box[0]:focus_bounding_box[0]+focus_bounding_box[2]]
cropped_resized_image_data, _dim = maintain_aspect_ratio_resize(cropped_image_data, width=classifier_resolution)
cropped_resized_blurred_image_data = cv2.GaussianBlur(cropped_resized_image_data,(3,3),0)

all_images_dict[classification].append(cropped_resized_blurred_image_data.flatten().tolist())
with open(os.getenv("APP_DIR") + "/blanket_model/output/image_data.json", "w") as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + "/blanket_model/output/image_data.json", "w") as f:
json.dump(all_images_dict, f)

# flatten all_fds
Expand All @@ -971,10 +971,10 @@ def retrainWithNewSample(classification):
# final_clf = svm.SVC(probability=True, C=1.0, gamma='auto', kernel='rbf')
final_clf.fit(all_images_flat, all_labels)

with open(os.getenv("APP_DIR") + '/blanket_model/creepy_baby_model.pkl','wb') as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/creepy_baby_model.pkl','wb') as f:
pickle.dump(final_clf,f)

with open(os.getenv("APP_DIR") + '/blanket_model/creepy_baby_model.pkl', 'rb') as f:
with open(os.getenv("APP_DIR", "/usr/app/babysleepcoach") + '/blanket_model/creepy_baby_model.pkl', 'rb') as f:
creepy_baby_model = pickle.load(f)

except Exception as e:
Expand Down Expand Up @@ -1028,4 +1028,4 @@ def receive(producer_q):
# TODO:
# - display cause of speedometer 'ticks' in app somewhere
# - draw more stuff on debug image
# - refactor crazy circles chart to be zoomable and scale
# - refactor crazy circles chart to be zoomable and scale