adding mvp backend

Dockerfile

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+# Start with Python 3.9
+FROM python:3.9
+
+# Install system libraries required for OpenCV
+RUN apt-get update && apt-get install -y libgl1-mesa-glx
+
+# Set working directory
+WORKDIR /code
+
+# Copy requirements and install dependencies
+COPY ./requirements.txt /code/requirements.txt
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# Create a writable directory for YOLO weights & temporary files
+# Hugging Face runs as user 1000, so we must give permission
+RUN mkdir -p /code/temp_files && chmod 777 /code/temp_files
+
+# Copy the rest of the code
+COPY . .
+
+# Start the server on port 7860
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

main.py

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+from fastapi import FastAPI, UploadFile, File
+from fastapi.responses import FileResponse
+from ultralytics import YOLO
+import shutil
+import os
+
+app = FastAPI()
+
+# Load the model (Nano version is best for free CPU tier)
+model = YOLO('yolov8n.pt') 
+
+# Define paths
+TEMP_FOLDER = "temp_files"
+os.makedirs(TEMP_FOLDER, exist_ok=True)
+
+@app.get("/")
+def home():
+    return {"message": "YOLOv8 Tracking API is Active"}
+
+@app.post("/track-video")
+async def track_video(file: UploadFile = File(...)):
+    # 1. Define paths
+    input_path = os.path.join(TEMP_FOLDER, "input.mp4")
+    
+    # 2. Save uploaded video to disk
+    with open(input_path, "wb") as buffer:
+        shutil.copyfileobj(file.file, buffer)
+        
+    # 3. Run YOLOv8 Tracking
+    # project=TEMP_FOLDER ensures output saves to our writable directory
+    # name='result' creates a subfolder
+    results = model.track(source=input_path, save=True, project=TEMP_FOLDER, name="tracking_result", exist_ok=True)
+    
+    # YOLO usually saves as .avi by default. 
+    # The output path will be something like: temp_files/tracking_result/input.avi
+    output_video_path = os.path.join(TEMP_FOLDER, "tracking_result", "input.avi")
+
+    # 4. Return the processed video file
+    return FileResponse(output_video_path, media_type="video/x-msvideo", filename="tracked_video.avi")

requirements.txt

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+fastapi
+python-multipart
+uvicorn
+easyocr
+numpy
+opencv-python-headless
+ultralytics