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#!/usr/bin/env python3
"""
Test the encoding fix for CNN model outputs
"""
import sys
import os
from io import BytesIO
from PIL import Image
# Add current directory to path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
def test_encoding_fix():
"""Test if the encoding issue is fixed"""
print("Testing Encoding Fix for CNN Model")
print("=" * 40)
try:
from local_models import get_local_model_manager
from app import extract_frames_from_video, process_image_locally
print("+ Successfully imported components")
except ImportError as e:
print(f"- Import error: {e}")
return
# 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
video_path = video_files[0]
print(f"+ Using video: {video_path[:50]}...")
# Initialize models
try:
local_manager = get_local_model_manager()
print("+ Models initialized")
except Exception as e:
print(f"- Model error: {e}")
return
# Extract one frame for testing
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=0.1) # Just first frame
if not frames:
print("- No frames extracted")
return
test_frame = frames[0]['frame']
print("+ Extracted test frame")
except Exception as e:
print(f"- Frame extraction error: {e}")
return
# Test CNN model with cleaned output
print("\nTesting CNN (BLIP) with encoding fix:")
print("-" * 40)
try:
result = process_image_locally(
test_frame,
"Describe what you see",
'CNN (BLIP)',
local_manager
)
if 'error' in result:
print(f"- Error: {result['error']}")
else:
caption = result.get('generated_text', 'No caption')
print(f"+ Result: {caption}")
# Check for problematic characters
has_issues = False
for char in caption:
if ord(char) > 127:
print(f"- Found non-ASCII character: {repr(char)} (ord: {ord(char)})")
has_issues = True
if not has_issues:
print("+ No encoding issues detected!")
else:
print("- Still has encoding issues")
except Exception as e:
print(f"- Exception: {e}")
# Test Transformer for comparison
print("\nTesting Transformer (ViT-GPT2) for comparison:")
print("-" * 40)
try:
result = process_image_locally(
test_frame,
"Describe what you see",
'Transformer (ViT-GPT2)',
local_manager
)
if 'error' in result:
print(f"- Error: {result['error']}")
else:
caption = result.get('generated_text', 'No caption')
print(f"+ Result: {caption}")
except Exception as e:
print(f"- Exception: {e}")
if __name__ == "__main__":
test_encoding_fix() |