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#!/usr/bin/env python3
"""
Automated test for video processing with local AI models
"""
import sys
import os
from io import BytesIO
# Add current directory to path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
def test_full_pipeline():
"""Test the complete video processing pipeline"""
print("Automated Video + AI Processing Test")
print("=" * 40)
# Test imports
try:
from app import extract_frames_from_video, process_image_locally
from local_models import get_local_model_manager
print("+ App components imported successfully")
except ImportError as e:
print(f"- Import error: {e}")
return False
# Find video file
video_files = [f for f in os.listdir('.') if f.endswith('.mp4')]
if not video_files:
print("- No MP4 files found")
return False
video_path = video_files[0]
print(f"+ Found video: {video_path[:50]}...")
# Initialize models
print("+ Initializing AI models...")
try:
local_manager = get_local_model_manager()
available_models = local_manager.get_available_models()
print(f"+ Available models: {available_models}")
except Exception as e:
print(f"- Model initialization error: {e}")
return False
# Extract frames
print("+ Extracting video frames...")
try:
with open(video_path, 'rb') as f:
video_data = f.read()
video_file = BytesIO(video_data)
frames = extract_frames_from_video(video_file, fps=0.2) # 1 frame every 5 seconds
if not frames:
print("- No frames extracted")
return False
print(f"+ Extracted {len(frames)} frames")
# Test with first 2 frames only
test_frames = frames[:2]
except Exception as e:
print(f"- Frame extraction error: {e}")
return False
# Test both models
test_prompt = "Describe what you see"
success_count = 0
for model_name in available_models:
print(f"\nTesting {model_name}...")
try:
# Test with first frame only to save time
frame_data = test_frames[0]
result = process_image_locally(
frame_data['frame'],
test_prompt,
model_name,
local_manager
)
if 'error' in result:
print(f" - Error: {result['error']}")
else:
caption = result.get('generated_text', 'No caption')
print(f" + Success: {caption[:50]}...")
success_count += 1
except Exception as e:
print(f" - Exception: {e}")
# Final results
print("\n" + "=" * 40)
print("RESULTS")
print("=" * 40)
if success_count > 0:
print(f"+ SUCCESS: {success_count}/{len(available_models)} models working")
print("+ Your video processing setup is ready!")
print("+ Visit http://localhost:8502 to use the full app")
return True
else:
print("- FAILED: No models processed successfully")
return False
if __name__ == "__main__":
success = test_full_pipeline()
if success:
print("\n+ All tests passed! Local AI video processing is working!")
else:
print("\n- Some tests failed. Check error messages above.")
print("\nNext steps:")
print("1. Open http://localhost:8502")
print("2. Select 'Local Models' in sidebar")
print("3. Choose CNN or Transformer model")
print("4. Upload your video and test!") |