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update video_gen and Cloudflare upload to use avc1 codec
Browse files- README.md +13 -35
- __pycache__/app.cpython-311.pyc +0 -0
- __pycache__/video_gen.cpython-311.pyc +0 -0
- app.py +54 -10
- test_h264_encoding.py +152 -0
- video_gen.py +47 -6
README.md
CHANGED
@@ -14,7 +14,7 @@ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-
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# AI-SL API
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-
Convert
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## Features
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@@ -22,15 +22,13 @@ Convert text documents to American Sign Language (ASL) videos using AI.
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The app accepts both text input and file uploads with flexible options:
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- **Text Input**: Type or paste text directly into the interface (always available)
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-
- **File Upload**: Upload documents (PDF, TXT, DOCX, EPUB)
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-
- **Smart Priority**: Text input takes priority if both are provided
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-
- **Toggle Control**: Checkbox to enable/disable file upload functionality
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### Video Output Options
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The Gradio interface provides multiple ways for users to receive and download the generated ASL videos:
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#### 1. R2 Cloud Storage
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- Videos are automatically uploaded to Cloudflare R2 storage
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- Returns a public URL that users can download directly
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- Videos persist and can be shared via URL
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api_name="/predict"
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)
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# The result contains: (json_data, video_output
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json_data, video_url
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# Download the video
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import requests
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@@ -67,11 +65,6 @@ with open("asl_video.mp4", "wb") as f:
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f.write(response.content)
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```
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#### 4. Direct Download from Interface
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- The interface includes a styled download button
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- Users can right-click and "Save As" if automatic download doesn't work
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- Video files are named `asl_video.mp4` by default
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-
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## Example Usage
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### Web Interface
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@@ -79,7 +72,7 @@ with open("asl_video.mp4", "wb") as f:
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2. Choose input method:
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- **Text**: Type or paste text in the text box (always available)
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- **File**: Check "Enable file upload" and upload a document (optional)
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3. Click "
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4. Download the resulting video
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### Programmatic Access with Optional File Upload
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@@ -88,37 +81,32 @@ with open("asl_video.mp4", "wb") as f:
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from gradio_client import Client
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# Connect to your hosted app
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-
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# Text input only (file upload disabled)
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result = client.predict(
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"Hello world! This is a test.", # Text input
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-
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None, # File input (None since disabled)
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True, # Use R2 storage
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api_name="/predict"
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)
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# File input only (file upload enabled)
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result = client.predict(
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"", # Text input (empty)
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-
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"document.pdf", # File input
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True, # Use R2 storage
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api_name="/predict"
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)
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# Both inputs (text takes priority)
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result = client.predict(
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"Quick text", # Text input
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True, # Enable file upload (True = enabled)
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"document.pdf", # File input
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True, # Use R2 storage
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api_name="/predict"
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)
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```
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-
See `example_usage.py
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- Download videos from URLs
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- Process base64 video data
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- Use the interface programmatically
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@@ -147,13 +135,3 @@ Once you have the video file, you can:
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- Convert to different formats
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- Extract frames for further processing
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- Add subtitles or overlays
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-
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## Deployment to Hugging Face Spaces
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-
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1. Create a new Space on Hugging Face
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2. Choose Gradio as the SDK
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3. Upload your code files
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4. Set environment variables in Space settings
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5. Deploy and share your Space URL
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-
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Your app will be accessible to users worldwide with flexible input options!
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# AI-SL API
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+
Convert natural language English into American Sign Language (ASL) videos using AI.
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## Features
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20 |
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The app accepts both text input and file uploads with flexible options:
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- **Text Input**: Type or paste text directly into the interface (always available)
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+
- **File Upload**: Upload documents (PDF, TXT, DOCX, EPUB)
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### Video Output Options
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The Gradio interface provides multiple ways for users to receive and download the generated ASL videos:
|
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+
#### 1. R2 Cloud Storage
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- Videos are automatically uploaded to Cloudflare R2 storage
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- Returns a public URL that users can download directly
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- Videos persist and can be shared via URL
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api_name="/predict"
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)
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# The result contains: (json_data, video_output)
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json_data, video_url = result
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# Download the video
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import requests
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f.write(response.content)
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```
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## Example Usage
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### Web Interface
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2. Choose input method:
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- **Text**: Type or paste text in the text box (always available)
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- **File**: Check "Enable file upload" and upload a document (optional)
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+
3. Click "Submit"
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4. Download the resulting video
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### Programmatic Access with Optional File Upload
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from gradio_client import Client
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# Connect to your hosted app
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from gradio_client import Client, handle_file
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client = Client("deenasun/ai-sl-api")
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# Text input only (file upload disabled)
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result = client.predict(
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text="Hello world! This is a test.", # Text input
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file=None, # File input (None since disabled)
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api_name="/predict"
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)
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# File input only (file upload enabled)
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result = client.predict(
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text="", # Text input (empty)
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file=handle_file("document.pdf"), # File input
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api_name="/predict"
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)
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# Both inputs (text takes priority)
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result = client.predict(
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"Quick text", # Text input
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"document.pdf", # File input
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api_name="/predict"
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)
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```
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+
See `example_usage.py` and `example_usage_dual_input.py` for complete examples of how to:
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- Download videos from URLs
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- Process base64 video data
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- Use the interface programmatically
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- Convert to different formats
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136 |
- Extract frames for further processing
|
137 |
- Add subtitles or overlays
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__pycache__/app.cpython-311.pyc
CHANGED
Binary files a/__pycache__/app.cpython-311.pyc and b/__pycache__/app.cpython-311.pyc differ
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__pycache__/video_gen.cpython-311.pyc
CHANGED
Binary files a/__pycache__/video_gen.cpython-311.pyc and b/__pycache__/video_gen.cpython-311.pyc differ
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app.py
CHANGED
@@ -70,11 +70,41 @@ def clean_gloss_token(token):
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return cleaned if cleaned else None
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def upload_video_to_r2(video_path, bucket_name="asl-videos"):
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"""
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Upload a video file to R2 and return a public URL
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"""
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try:
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# Generate a unique filename
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file_extension = os.path.splitext(video_path)[1]
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unique_filename = f"{uuid.uuid4()}{file_extension}"
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@@ -87,22 +117,26 @@ def upload_video_to_r2(video_path, bucket_name="asl-videos"):
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unique_filename,
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ExtraArgs={
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'ACL': 'public-read',
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-
'ContentType': 'video/mp4',
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'CacheControl': 'max-age=86400', # Cache for 24 hours
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'ContentDisposition': 'inline' # Force inline display
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})
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# Replace the endpoint with the domain for uploading
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-
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-
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-
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-
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-
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-
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-
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except Exception as e:
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print(f"Error uploading video to R2: {e}")
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@@ -171,6 +205,16 @@ def determine_input_type(input_data):
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# Check if it's a file path (contains file extension)
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if any(ext in input_data.lower() for ext in ['.pdf', '.txt', '.docx', '.doc', '.epub']):
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return 'file_path', input_data
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else:
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return 'text', input_data.strip()
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elif isinstance(input_data, dict) and 'path' in input_data:
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@@ -312,7 +356,7 @@ def predict_unified(input_data):
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"message": "Please provide text or upload a document"
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}, None
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-
print("Input", input_data)
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# Use the unified processing function
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result = parse_vectorize_and_search_unified_sync(input_data)
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return cleaned if cleaned else None
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+
def verify_video_format(video_path):
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"""
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Verify that a video file is in a browser-compatible format (H.264 MP4)
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"""
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try:
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import cv2
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cap = cv2.VideoCapture(video_path)
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if not cap.isOpened():
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return False, "Could not open video file"
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+
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# Get video properties
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fourcc = int(cap.get(cv2.CAP_PROP_FOURCC))
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codec = "".join([chr((fourcc >> 8 * i) & 0xFF) for i in range(4)])
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+
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cap.release()
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+
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# Check if it's H.264
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if codec in ['avc1', 'H264', 'h264']:
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return True, f"Video is H.264 encoded ({codec})"
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else:
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return False, f"Video codec {codec} may not be browser compatible"
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+
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except Exception as e:
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return False, f"Error checking video format: {e}"
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+
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+
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def upload_video_to_r2(video_path, bucket_name="asl-videos"):
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"""
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Upload a video file to R2 and return a public URL
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"""
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try:
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# Verify video format for browser compatibility
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is_compatible, message = verify_video_format(video_path)
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print(f"Video format check: {message}")
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+
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# Generate a unique filename
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file_extension = os.path.splitext(video_path)[1]
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unique_filename = f"{uuid.uuid4()}{file_extension}"
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unique_filename,
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ExtraArgs={
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'ACL': 'public-read',
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+
'ContentType': 'video/mp4; codecs="avc1.42E01E"', # H.264
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'CacheControl': 'max-age=86400', # Cache for 24 hours
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'ContentDisposition': 'inline' # Force inline display
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})
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# Replace the endpoint with the domain for uploading
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+
if R2_ENDPOINT:
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public_domain = (R2_ENDPOINT.replace('https://', '')
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+
.split('.')[0])
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video_url = (f"https://{public_domain}.r2.cloudflarestorage.com/"
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f"{bucket_name}/{unique_filename}")
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print(f"Video uploaded to R2: {video_url}")
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public_video_url = f"{R2_ASL_VIDEOS_URL}/{unique_filename}"
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print(f"Public video url: {public_video_url}")
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return public_video_url
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else:
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print("R2_ENDPOINT is not configured")
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return None
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except Exception as e:
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print(f"Error uploading video to R2: {e}")
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# Check if it's a file path (contains file extension)
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if any(ext in input_data.lower() for ext in ['.pdf', '.txt', '.docx', '.doc', '.epub']):
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return 'file_path', input_data
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+
# Check if it's a string representation of a gradio.FileData dict
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+
elif input_data.startswith('{') and 'gradio.FileData' in input_data:
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try:
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import ast
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# Safely evaluate the string as a dictionary
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file_data = ast.literal_eval(input_data)
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if isinstance(file_data, dict) and 'path' in file_data:
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return 'file_path', file_data['path']
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except (ValueError, SyntaxError):
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pass
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else:
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return 'text', input_data.strip()
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elif isinstance(input_data, dict) and 'path' in input_data:
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"message": "Please provide text or upload a document"
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}, None
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+
print("Input", input_data, type(input_data))
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# Use the unified processing function
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result = parse_vectorize_and_search_unified_sync(input_data)
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test_h264_encoding.py
ADDED
@@ -0,0 +1,152 @@
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#!/usr/bin/env python3
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"""
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+
Test script to verify H.264 video encoding for browser compatibility
|
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+
"""
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+
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+
import cv2
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7 |
+
import numpy as np
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+
import tempfile
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+
import os
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10 |
+
from video_gen import get_video_writer
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+
from app import verify_video_format
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+
|
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+
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+
def test_h264_encoding():
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+
"""Test H.264 video encoding and verify browser compatibility"""
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+
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print("Testing H.264 video encoding for browser compatibility...")
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+
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+
# Create a simple test video
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+
temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
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+
temp_path = temp_file.name
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+
temp_file.close()
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+
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+
try:
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+
# Create a simple test video with colored rectangles
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+
out = get_video_writer(temp_path, fps=30.0, width=640, height=480)
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+
|
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+
if not out.isOpened():
|
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+
print("ERROR: Could not create video writer")
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30 |
+
return False
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31 |
+
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32 |
+
# Create 3 seconds of video (90 frames at 30 fps)
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33 |
+
for frame_num in range(90):
|
34 |
+
# Create a frame with changing colors
|
35 |
+
frame = np.zeros((480, 640, 3), dtype=np.uint8)
|
36 |
+
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37 |
+
# Create a moving colored rectangle
|
38 |
+
color = (
|
39 |
+
int(255 * (frame_num % 30) / 30), # Red
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40 |
+
int(255 * ((frame_num + 10) % 30) / 30), # Green
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41 |
+
int(255 * ((frame_num + 20) % 30) / 30) # Blue
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42 |
+
)
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43 |
+
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44 |
+
# Draw a rectangle that moves across the screen
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45 |
+
x = int((frame_num % 60) * 640 / 60)
|
46 |
+
cv2.rectangle(frame, (x, 200), (x + 100, 300), color, -1)
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47 |
+
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48 |
+
# Add text
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49 |
+
cv2.putText(frame, f"Frame {frame_num}", (50, 50),
|
50 |
+
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
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51 |
+
|
52 |
+
out.write(frame)
|
53 |
+
|
54 |
+
out.release()
|
55 |
+
|
56 |
+
# Verify the video format
|
57 |
+
is_compatible, message = verify_video_format(temp_path)
|
58 |
+
print(f"Video format verification: {message}")
|
59 |
+
|
60 |
+
if is_compatible:
|
61 |
+
print("✅ SUCCESS: Video is H.264 encoded and browser compatible!")
|
62 |
+
|
63 |
+
# Get video info
|
64 |
+
cap = cv2.VideoCapture(temp_path)
|
65 |
+
fps = cap.get(cv2.CAP_PROP_FPS)
|
66 |
+
frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
|
67 |
+
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
|
68 |
+
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
|
69 |
+
cap.release()
|
70 |
+
|
71 |
+
print(f"Video properties:")
|
72 |
+
print(f" - Resolution: {width}x{height}")
|
73 |
+
print(f" - FPS: {fps}")
|
74 |
+
print(f" - Frame count: {frame_count}")
|
75 |
+
print(f" - Duration: {frame_count/fps:.2f} seconds")
|
76 |
+
print(f" - File size: {os.path.getsize(temp_path)} bytes")
|
77 |
+
|
78 |
+
return True
|
79 |
+
else:
|
80 |
+
print("❌ FAILED: Video is not browser compatible")
|
81 |
+
return False
|
82 |
+
|
83 |
+
except Exception as e:
|
84 |
+
print(f"❌ ERROR: {e}")
|
85 |
+
return False
|
86 |
+
finally:
|
87 |
+
# Clean up
|
88 |
+
if os.path.exists(temp_path):
|
89 |
+
os.unlink(temp_path)
|
90 |
+
print(f"Cleaned up test file: {temp_path}")
|
91 |
+
|
92 |
+
|
93 |
+
def test_codec_availability():
|
94 |
+
"""Test which video codecs are available"""
|
95 |
+
|
96 |
+
print("\nTesting available video codecs...")
|
97 |
+
|
98 |
+
codecs_to_test = [
|
99 |
+
('avc1', 'H.264 (best for browsers)'),
|
100 |
+
('mp4v', 'MPEG-4'),
|
101 |
+
('XVID', 'XVID'),
|
102 |
+
('MJPG', 'Motion JPEG'),
|
103 |
+
('H264', 'H.264 alternative')
|
104 |
+
]
|
105 |
+
|
106 |
+
temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
|
107 |
+
temp_path = temp_file.name
|
108 |
+
temp_file.close()
|
109 |
+
|
110 |
+
available_codecs = []
|
111 |
+
|
112 |
+
for codec_name, description in codecs_to_test:
|
113 |
+
try:
|
114 |
+
fourcc = cv2.VideoWriter_fourcc(*codec_name)
|
115 |
+
out = cv2.VideoWriter(temp_path, fourcc, 30.0, (640, 480))
|
116 |
+
|
117 |
+
if out.isOpened():
|
118 |
+
available_codecs.append((codec_name, description))
|
119 |
+
print(f"✅ {codec_name}: {description}")
|
120 |
+
out.release()
|
121 |
+
else:
|
122 |
+
print(f"❌ {codec_name}: {description} (not working)")
|
123 |
+
out.release()
|
124 |
+
|
125 |
+
except Exception as e:
|
126 |
+
print(f"❌ {codec_name}: {description} (error: {e})")
|
127 |
+
|
128 |
+
# Clean up
|
129 |
+
if os.path.exists(temp_path):
|
130 |
+
os.unlink(temp_path)
|
131 |
+
|
132 |
+
print(f"\nAvailable codecs: {len(available_codecs)}")
|
133 |
+
return available_codecs
|
134 |
+
|
135 |
+
|
136 |
+
if __name__ == "__main__":
|
137 |
+
print("=" * 60)
|
138 |
+
print("H.264 Video Encoding Test for Browser Compatibility")
|
139 |
+
print("=" * 60)
|
140 |
+
|
141 |
+
# Test available codecs
|
142 |
+
available_codecs = test_codec_availability()
|
143 |
+
|
144 |
+
# Test H.264 encoding
|
145 |
+
success = test_h264_encoding()
|
146 |
+
|
147 |
+
print("\n" + "=" * 60)
|
148 |
+
if success:
|
149 |
+
print("🎉 All tests passed! Videos should work in Chrome and Firefox.")
|
150 |
+
else:
|
151 |
+
print("⚠️ Some tests failed. Check the output above for details.")
|
152 |
+
print("=" * 60)
|
video_gen.py
CHANGED
@@ -462,14 +462,56 @@ def interpolate_keypoints(kptsA, kptsB, steps):
|
|
462 |
frames.append((interp_pose, interp_left, interp_right))
|
463 |
return frames
|
464 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
465 |
def create_stitched_video(videoA_path, videoB_path, output_path="stitched_output.mp4"):
|
466 |
# Extract keypoints from both videos
|
467 |
videoA_keypoints = extract_keypoints_from_video(videoA_path)
|
468 |
videoB_keypoints = extract_keypoints_from_video(videoB_path)
|
469 |
|
470 |
-
# Create video writer
|
471 |
-
|
472 |
-
out = cv2.VideoWriter(output_path, fourcc, 30.0, (1280, 720))
|
473 |
|
474 |
# Show original A
|
475 |
for pose, l, r in videoA_keypoints:
|
@@ -513,9 +555,8 @@ def create_multi_stitched_video(video_paths, output_path="multi_stitched_output.
|
|
513 |
all_keypoints.append(keypoints)
|
514 |
print(f" - Extracted {len(keypoints)} frames")
|
515 |
|
516 |
-
# Create video writer
|
517 |
-
|
518 |
-
out = cv2.VideoWriter(output_path, fourcc, 30.0, (1280, 720))
|
519 |
|
520 |
total_frames = 0
|
521 |
|
|
|
462 |
frames.append((interp_pose, interp_left, interp_right))
|
463 |
return frames
|
464 |
|
465 |
+
def get_video_writer(output_path, fps=30.0, width=1280, height=720):
|
466 |
+
"""
|
467 |
+
Create a video writer with H.264 codec for better browser compatibility.
|
468 |
+
Falls back to other codecs if H.264 is not available.
|
469 |
+
"""
|
470 |
+
# Try H.264 codec first (best for browser compatibility)
|
471 |
+
try:
|
472 |
+
fourcc = cv2.VideoWriter_fourcc(*'avc1')
|
473 |
+
out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
|
474 |
+
if out.isOpened():
|
475 |
+
print("Using H.264 (avc1) codec for video encoding")
|
476 |
+
return out
|
477 |
+
else:
|
478 |
+
out.release()
|
479 |
+
except Exception as e:
|
480 |
+
print(f"H.264 codec not available: {e}")
|
481 |
+
|
482 |
+
# Fallback to MPEG-4
|
483 |
+
try:
|
484 |
+
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
|
485 |
+
out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
|
486 |
+
if out.isOpened():
|
487 |
+
print("Using MPEG-4 (mp4v) codec for video encoding")
|
488 |
+
return out
|
489 |
+
else:
|
490 |
+
out.release()
|
491 |
+
except Exception as e:
|
492 |
+
print(f"MPEG-4 codec not available: {e}")
|
493 |
+
|
494 |
+
# Final fallback to XVID
|
495 |
+
try:
|
496 |
+
fourcc = cv2.VideoWriter_fourcc(*'XVID')
|
497 |
+
out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
|
498 |
+
if out.isOpened():
|
499 |
+
print("Using XVID codec for video encoding")
|
500 |
+
return out
|
501 |
+
else:
|
502 |
+
out.release()
|
503 |
+
except Exception as e:
|
504 |
+
print(f"XVID codec not available: {e}")
|
505 |
+
|
506 |
+
raise RuntimeError("No suitable video codec found")
|
507 |
+
|
508 |
def create_stitched_video(videoA_path, videoB_path, output_path="stitched_output.mp4"):
|
509 |
# Extract keypoints from both videos
|
510 |
videoA_keypoints = extract_keypoints_from_video(videoA_path)
|
511 |
videoB_keypoints = extract_keypoints_from_video(videoB_path)
|
512 |
|
513 |
+
# Create video writer with H.264 codec for better browser compatibility
|
514 |
+
out = get_video_writer(output_path, 30.0, 1280, 720)
|
|
|
515 |
|
516 |
# Show original A
|
517 |
for pose, l, r in videoA_keypoints:
|
|
|
555 |
all_keypoints.append(keypoints)
|
556 |
print(f" - Extracted {len(keypoints)} frames")
|
557 |
|
558 |
+
# Create video writer with H.264 codec for better browser compatibility
|
559 |
+
out = get_video_writer(output_path, 30.0, 1280, 720)
|
|
|
560 |
|
561 |
total_frames = 0
|
562 |
|