Update app.py

app.py

@@ -8,20 +8,19 @@ import cv2
 import io
 from datetime import datetime, timedelta
 from collections import defaultdict
-import os
 
-app = FastAPI(title="Backdrop Studio API", version="2.0.0")
+app = FastAPI(title="MODNet API", version="1.0.0")
 
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["*"],  # Restrict for production!
+    allow_origins=["*"],
     allow_credentials=True,
     allow_methods=["*"],
     allow_headers=["*"],
 )
 
-MODEL_PATH = "models/modnet.onnx"
-MODEL_WIDTH = 512   # Official MODNet ONNX input size (for best speed, use 512; 768 or 1024 for higher res if model supports)
+MODEL_PATH = "modnet.onnx"   # model ONNX is in root folder!
+MODEL_WIDTH = 512
 MODEL_HEIGHT = 512
 
 print("🔄 Loading MODNet ONNX model...")
@@ -47,17 +46,15 @@ def preprocess_image(image: Image.Image, target_size=(MODEL_WIDTH, MODEL_HEIGHT)
         image = image.convert('RGB')
     orig_width, orig_height = image.size
     image_resized = image.resize(target_size, Image.LANCZOS)
-    img_array = np.array(image_resized).astype(np.float32) / 255.0  # shape (512, 512, 3)
-    img_array = np.transpose(img_array, (2, 0, 1))  # (3, 512, 512)
-    img_array = np.expand_dims(img_array, axis=0)   # (1, 3, 512, 512)
+    img_array = np.array(image_resized).astype(np.float32) / 255.0
+    img_array = np.transpose(img_array, (2, 0, 1))
+    img_array = np.expand_dims(img_array, axis=0)
     return img_array, (orig_width, orig_height)
 
 def postprocess_mask(mask: np.ndarray, original_size):
-    # MODNet returns (1,1,H,W) float in [0,1]
-    mask = mask[0, 0]  # (H,W)
+    mask = mask[0, 0]
     mask = (mask * 255).round().astype(np.uint8)
     mask = cv2.resize(mask, original_size, interpolation=cv2.INTER_LINEAR)
-    # Optional: Apply threshold to get crisp mask
     mask = np.where(mask > 127, 255, 0).astype(np.uint8)
     return mask
 
@@ -73,7 +70,7 @@ def remove_background(image: Image.Image):
 
 @app.get("/")
 async def root():
-    return {"status": "healthy", "service": "Backdrop Studio MODNet API", "version": "2.0.0"}
+    return {"status": "healthy", "service": "MODNet API", "version": "1.0.0"}
 
 @app.get("/quota/{user_id}")
 async def get_quota(user_id: str):
@@ -137,5 +134,4 @@ async def remove_background_endpoint(
 
 if __name__ == "__main__":
     import uvicorn
-    port = int(os.environ.get("PORT", 8080))
-    uvicorn.run(app, host="0.0.0.0", port=port)
+    uvicorn.run(app, host="0.0.0.0", port=7860)