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Itoshi321/
road_damage

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from fastapi import FastAPI, UploadFile, File from ultralytics import YOLO import cv2 import numpy as np import shutil from fastapi.responses import JSONResponse import os

app = FastAPI()

Load the trained model

MODEL_PATH = "pothole_best.pt" model = YOLO(MODEL_PATH)

@app.post("/predict/") async def predict(file: UploadFile = File(...)): try: # Save uploaded file file_path = f"temp_{file.filename}" with open(file_path, "wb") as buffer: shutil.copyfileobj(file.file, buffer)

    # Read video
    cap = cv2.VideoCapture(file_path)
    frame_results = []

    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break

        results = model(frame)  # Run YOLO inference
        detections = results.pandas().xyxy[0].to_dict(orient="records")
        frame_results.append(detections)
    
    cap.release()
    os.remove(file_path)
    
    return JSONResponse(content={"detections": frame_results})
except Exception as e:
    return JSONResponse(content={"error": str(e)}, status_code=500)

Itoshi321/road_damage

Load the trained model

Itoshi321/
road_damage