MAJOR UPDATE: Fix REAL AI + Add Video Export!

FIX 1 - REAL AI MODELS WORKING:
- Fix huggingface-hub version constraint to <1.0
- Error was: huggingface-hub==1.0.1 incompatible with transformers
- Now: huggingface-hub>=0.26.0,<1.0 (compatible)
- BASE model (372MB) will now load successfully!

FIX 2 - VIDEO EXPORT ADDED:
- Duration control (1-10 seconds)
- FPS selection (24/30/60)
- Resolution options (Original/1080p/720p/Square 1080p)
- Camera effects:
* Zoom In - Smooth zoom 1x to 1.5x
* Zoom Out - Smooth zoom 1.5x to 1x
* Pan Left - Pan camera left
* Pan Right - Pan camera right
* Rotate - 360 degree rotation
- Download button for MP4 export

This gives you BOTH features you wanted!

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <[email protected]>

app.py

@@ -157,6 +157,112 @@ if uploaded_file is not None and process_btn:
 {f'**Powered by**: Depth-Anything V2 {MODEL_SIZE}' if USE_REAL_AI else '**Processing**: Ultra-fast (<50ms) synthetic depth'}
         """)
 
+# Video Export Section
+st.markdown("---")
+st.subheader("🎬 Video Export")
+
+if uploaded_file is not None and depth_colored is not None:
+    with st.expander("Export Depth Map as Video"):
+        col_vid1, col_vid2 = st.columns(2)
+
+        with col_vid1:
+            video_duration = st.slider("Duration (seconds)", 1, 10, 3)
+            video_fps = st.selectbox("FPS", [24, 30, 60], index=1)
+
+        with col_vid2:
+            video_resolution = st.selectbox("Resolution", ["Original", "1080p", "720p", "Square 1080p"])
+            video_effect = st.selectbox("Effect", ["Zoom In", "Zoom Out", "Pan Left", "Pan Right", "Rotate"])
+
+        if st.button("🎬 Export Video", type="primary"):
+            with st.spinner("Generating video..."):
+                try:
+                    import cv2
+                    import tempfile
+
+                    # Get dimensions
+                    if video_resolution == "1080p":
+                        width, height = 1920, 1080
+                    elif video_resolution == "720p":
+                        width, height = 1280, 720
+                    elif video_resolution == "Square 1080p":
+                        width, height = 1080, 1080
+                    else:
+                        height, width = depth_colored.shape[:2]
+
+                    # Resize depth map
+                    depth_resized = cv2.resize(depth_colored, (width, height))
+
+                    # Create video
+                    total_frames = video_duration * video_fps
+
+                    with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as tmp_file:
+                        output_path = tmp_file.name
+
+                    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+                    out = cv2.VideoWriter(output_path, fourcc, video_fps, (width, height))
+
+                    for frame_num in range(total_frames):
+                        progress = frame_num / total_frames
+
+                        # Apply effect
+                        if video_effect == "Zoom In":
+                            scale = 1.0 + (progress * 0.5)  # Zoom from 1x to 1.5x
+                            center_x, center_y = width // 2, height // 2
+                            new_w, new_h = int(width / scale), int(height / scale)
+                            x1, y1 = center_x - new_w // 2, center_y - new_h // 2
+                            x2, y2 = x1 + new_w, y1 + new_h
+                            cropped = depth_resized[max(0, y1):min(height, y2), max(0, x1):min(width, x2)]
+                            frame = cv2.resize(cropped, (width, height))
+
+                        elif video_effect == "Zoom Out":
+                            scale = 1.5 - (progress * 0.5)  # Zoom from 1.5x to 1x
+                            center_x, center_y = width // 2, height // 2
+                            new_w, new_h = int(width / scale), int(height / scale)
+                            x1, y1 = center_x - new_w // 2, center_y - new_h // 2
+                            x2, y2 = x1 + new_w, y1 + new_h
+                            cropped = depth_resized[max(0, y1):min(height, y2), max(0, x1):min(width, x2)]
+                            frame = cv2.resize(cropped, (width, height))
+
+                        elif video_effect == "Pan Left":
+                            offset = int(width * progress * 0.3)
+                            frame = np.roll(depth_resized, -offset, axis=1)
+
+                        elif video_effect == "Pan Right":
+                            offset = int(width * progress * 0.3)
+                            frame = np.roll(depth_resized, offset, axis=1)
+
+                        elif video_effect == "Rotate":
+                            angle = progress * 360
+                            center = (width // 2, height // 2)
+                            rotation_matrix = cv2.getRotationMatrix2D(center, angle, 1.0)
+                            frame = cv2.warpAffine(depth_resized, rotation_matrix, (width, height))
+
+                        else:
+                            frame = depth_resized.copy()
+
+                        # Convert RGB to BGR for cv2
+                        frame_bgr = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
+                        out.write(frame_bgr)
+
+                    out.release()
+
+                    # Read video and provide download
+                    with open(output_path, 'rb') as f:
+                        video_bytes = f.read()
+
+                    st.success(f"✅ Video generated! {total_frames} frames at {video_fps} FPS")
+                    st.download_button(
+                        label="📥 Download Video",
+                        data=video_bytes,
+                        file_name=f"depth_video_{video_effect.lower().replace(' ', '_')}.mp4",
+                        mime="video/mp4"
+                    )
+
+                except Exception as e:
+                    st.error(f"Error generating video: {str(e)}")
+                    import traceback
+                    traceback.print_exc()
+
 # Info section
 st.markdown("---")
 st.markdown("""
@@ -167,6 +273,7 @@ st.markdown("""
 - ✅ Multiple colormap styles for visualization
 - ✅ Fast processing (~800ms on CPU, ~200ms on GPU)
 - ✅ SUPERB quality depth maps
+- ✅ **NEW!** Video export with camera effects
 
 ### Use Cases:
 - 🎨 **Creative & Artistic**: Depth-enhanced photos, 3D effects

requirements.txt

@@ -5,13 +5,13 @@ streamlit>=1.28.0
 torch>=2.0.0
 transformers>=4.30.0
 
+# For downloading models from HuggingFace - MUST BE < 1.0 for transformers compatibility!
+huggingface-hub>=0.26.0,<1.0
+
 # Core ML and image processing
 opencv-python==4.10.0.84
 Pillow>=8.0,<11.0
 numpy==1.26.4
 
-# For downloading models from HuggingFace
-huggingface-hub==0.27.0
-
 # Utilities
 python-dotenv==1.0.1