Update app.py

app.py

@@ -68,28 +68,36 @@ def load_text_model():
 def load_image_model():
     import os
     import tensorflow as tf
+    import requests
 
     model_path = "/tmp/image_detector_v2.h5"
 
-    if not os.path.exists(model_path):
-        import requests
-        print("Downloading model...")
-        url = "https://huggingface.co/Muniba930/image-detector/resolve/main/image_detector_v2.h5?download=true"
-        
-        with requests.get(url, stream=True) as r:
-            r.raise_for_status()
-            with open(model_path, "wb") as f:
-                for chunk in r.iter_content(chunk_size=8192):
-                    f.write(chunk)
+    # Always re-download (remove old corrupted file)
+    if os.path.exists(model_path):
+        os.remove(model_path)
+
+    url = "https://huggingface.co/Muniba930/image-detector/resolve/main/image_detector_v2.h5?download=true"
+    
+    with requests.get(url, stream=True, allow_redirects=True) as r:
+        r.raise_for_status()
         
-        # Verify file size
-        size_mb = os.path.getsize(model_path) / (1024 * 1024)
-        print(f"Downloaded: {size_mb:.1f} MB")
+        # Debug: show what we're getting
+        content_type = r.headers.get("Content-Type", "unknown")
+        content_length = r.headers.get("Content-Length", "unknown")
+        st.write(f"Debug → Content-Type: {content_type}, Size: {content_length} bytes")
         
-        if size_mb < 10:
-            os.remove(model_path)
-            st.error(f"Download failed — only {size_mb:.1f} MB received")
-            return None
+        with open(model_path, "wb") as f:
+            for chunk in r.iter_content(chunk_size=8192):
+                f.write(chunk)
+
+    size_mb = os.path.getsize(model_path) / (1024 * 1024)
+    st.write(f"Debug → Downloaded file size: {size_mb:.2f} MB")
+
+    # Check first bytes to verify it's a real HDF5 file
+    with open(model_path, "rb") as f:
+        header = f.read(8)
+    st.write(f"Debug → File header bytes: {header.hex()}")
+    # Real HDF5 file starts with: 894844460d0a1a0a
 
     model = tf.keras.models.load_model(model_path)
     return model