update app.py

app.py

@@ -1,47 +1,47 @@
-from fastapi import FastAPI, File, UploadFile
-from fastapi.responses import JSONResponse
-from fastapi.middleware.cors import CORSMiddleware
-from PIL import Image
-import io
-
-from pathlib import Path
-from model import YOLOModel
-import shutil
-
-yolo = YOLOModel()
-
-UPLOAD_FOLDER = Path("./uploads")
-UPLOAD_FOLDER.mkdir(exist_ok=True)
-
-app = FastAPI()
-
-@app.post("/upload")
-async def upload_image(image: UploadFile = File(...)):
-    # print(f'\n\t\tUPLOADED!!!!')
-    try:
-        file_path = UPLOAD_FOLDER / image.filename
-        with file_path.open("wb") as buffer:
-            shutil.copyfileobj(image.file, buffer)
-        # print(f'Starting to pass into model, {file_path}')
-        # Perform YOLO inference
-        predictions = yolo.predict(str(file_path))
-        # print(f'{predictions} \n\t\t\t\tare predictions')
-        # Clean up uploaded file
-        file_path.unlink()  # Remove file after processing
-        return JSONResponse(content={"items": predictions})
-    
-
-    except Exception as e:
-        return JSONResponse(content={"error": str(e)}, status_code=500)
-
-# code to accept the localhost to get images from
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["http://192.168.56.1:3000", "http://192.168.56.1:3001"],
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run("app:app", host="0.0.0.0", port=7860, reload=True)
+from fastapi import FastAPI, File, UploadFile
+from fastapi.responses import JSONResponse
+from fastapi.middleware.cors import CORSMiddleware
+from PIL import Image
+import io
+
+from pathlib import Path
+from model import YOLOModel
+import shutil
+
+yolo = YOLOModel()
+
+UPLOAD_FOLDER = Path("./uploads")
+UPLOAD_FOLDER.mkdir(exist_ok=True)
+
+app = FastAPI()
+
+@app.post("/upload")
+async def upload_image(image: UploadFile = File(...)):
+    # print(f'\n\t\tUPLOADED!!!!')
+    try:
+        file_path = UPLOAD_FOLDER / image.filename
+        with file_path.open("wb") as buffer:
+            shutil.copyfileobj(image.file, buffer)
+        # print(f'Starting to pass into model, {file_path}')
+        # Perform YOLO inference
+        predictions = yolo.predict(str(file_path))
+        print(f'\n\n\n{predictions}\n\n\ \n\t\t\t\tare predictions')
+        # Clean up uploaded file
+        file_path.unlink()  # Remove file after processing
+        return JSONResponse(content={"items": predictions})
+    
+
+    except Exception as e:
+        return JSONResponse(content={"error": str(e)}, status_code=500)
+
+# code to accept the localhost to get images from
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["http://192.168.56.1:3000", "http://192.168.56.1:3001"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run("app:app", host="0.0.0.0", port=7860, reload=True)