Update app.py

app.py

@@ -1,33 +1,33 @@
-from fastapi import FastAPI, UploadFile, File
-from fastapi.responses import JSONResponse
-from fastapi.staticfiles import StaticFiles
-from ultralytics import YOLO
-import shutil
-import uuid
-import base64
-import cv2
+from fastapi import FastAPI, BackgroundTasks
+import time
+import threading
 
 app = FastAPI()
 
-# Mount static frontend
-app.mount("/", StaticFiles(directory="static", html=True), name="static")
+task_running = False
+thread = None
 
-# Load YOLOv8 model
-model = YOLO("yolov8n.pt")  # Use your own trained model if needed
+def background_task():
+    while task_running:
+        print("Task running...")
+        time.sleep(2)
 
-@app.post("/detect")
-async def detect(file: UploadFile = File(...)):
-    # Save image to disk
-    file_name = f"uploads/{uuid.uuid4()}.jpg"
-    with open(file_name, "wb") as buffer:
-        shutil.copyfileobj(file.file, buffer)
+@app.get("/start")
+def start_task():
+    global task_running, thread
+    if not task_running:
+        task_running = True
+        thread = threading.Thread(target=background_task)
+        thread.start()
+        return {"message": "Task started"}
+    else:
+        return {"message": "Task already running"}
 
-    # Detect objects
-    results = model(file_name)
-    result_image = results[0].plot()  # Get image with boxes
-
-    # Encode image to base64 to send back
-    _, buffer = cv2.imencode('.jpg', result_image)
-    b64_encoded = base64.b64encode(buffer).decode('utf-8')
-
-    return JSONResponse(content={"image": b64_encoded})
+@app.get("/stop")
+def stop_task():
+    global task_running
+    if task_running:
+        task_running = False
+        return {"message": "Task stopped"}
+    else:
+        return {"message": "No task running"}