APEPDCL AI/ML Internship — Problem Statement Submission
Field images of plinth-mounted distribution transformer installations need to be automatically assessed for safety risk based on the clearance height between the transformer base and the ground. The accepted minimum safe clearance is 6 feet.
submission/
Phase1_Problem_Understanding.md
Phase2_Solution_Architecture.md
Phase3_Approach_Assumptions_RiskMethodology.md
Phase4_Evaluation_Strategy.md
EdgeCase_Handling.md
prototype/
dtr_risk_assessment.py main inference pipeline
train.py fine-tuning pipeline
prepare_dataset.py dataset splitting and YAML generation
evaluate.py metrics against ground truth
app.py Streamlit dashboard
requirements.txt
sample_outputs/ annotated results on provided sample images
cd prototype
pip3 install -r requirements.txt
Single image:
python3 dtr_risk_assessment.py sample_outputs/sample_image_1.jpg
Folder of images:
python3 dtr_risk_assessment.py --folder /path/to/images --output results/
python3 -m streamlit run app.py
Opens at http://localhost:8501
Live demo: https://apepdclinternship-ekfck3gvxsxlymxfrd6yxi.streamlit.app/
The dashboard has two modes:
- Sample images — select Image 1, Image 2, or run both and compare side by side. These are the two photographs provided in the problem statement PDF.
- Upload your own — drag and drop any field photograph and get the assessment back.
Each result shows the annotated image, risk label, estimated clearance in feet, confidence score, scale calibration method used, and flags for vegetation encroachment or manual review.
Six-stage pipeline: preprocessing → object detection (YOLOv8) → ground plane estimation → scale calibration → clearance calculation → risk classification.
Risk levels: Safe (≥ 6 ft) / Risky (4–6 ft) / Highly Risky (< 4 ft)
Vegetation encroachment and barrier absence can escalate the base classification. Low-confidence outputs are flagged for manual review rather than guessing.
Full methodology, assumptions, risk logic, edge case handling, and evaluation strategy are documented in the submission/ folder.
Tarigoppula Sree Sai Abhinav