Spaces:
Running
Running
File size: 3,075 Bytes
8a74c03 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 |
#!/usr/bin/env python3
"""
Test local models functionality
"""
import sys
import os
from PIL import Image
import numpy as np
# Add current directory to path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
try:
from local_models import LocalModelManager
print("✓ Successfully imported LocalModelManager")
except ImportError as e:
print(f"✗ Failed to import LocalModelManager: {e}")
print("Make sure torch and transformers are installed:")
print("pip install torch torchvision transformers accelerate sentencepiece")
sys.exit(1)
def test_local_models():
"""Test both CNN and Transformer models"""
print("Testing Local AI Models")
print("=" * 40)
# Initialize model manager
print("Initializing model manager...")
try:
manager = LocalModelManager()
print("✓ Model manager initialized")
except Exception as e:
print(f"✗ Failed to initialize model manager: {e}")
return
# Get available models
available_models = manager.get_available_models()
print(f"Available models: {available_models}")
# Create test images
test_images = [
("Blue Square", Image.new('RGB', (224, 224), color='blue')),
("Red Circle", Image.new('RGB', (224, 224), color='red')),
("Green Background", Image.new('RGB', (224, 224), color='green'))
]
test_prompt = "Describe what you see in this image"
# Test each model with each image
for model_name in available_models:
print(f"\n🤖 Testing {model_name}")
print("-" * 30)
for image_name, image in test_images:
print(f"Processing {image_name}...")
try:
result = manager.generate_caption(model_name, image, test_prompt)
print(f" Result: {result}")
except Exception as e:
print(f" ✗ Error: {e}")
print()
def test_model_info():
"""Test model information retrieval"""
print("\n📋 Model Information")
print("=" * 40)
try:
manager = LocalModelManager()
model_info = manager.get_model_info()
for model_name, info in model_info.items():
print(f"\n{model_name}:")
print(f" Description: {info['description']}")
print(f" Strengths: {info['strengths']}")
print(f" Size: {info['size']}")
except Exception as e:
print(f"✗ Error getting model info: {e}")
if __name__ == "__main__":
print("🧪 Local Models Test Suite")
print("This will download models on first run (~3GB total)")
print()
# Test model info first (doesn't require model downloads)
test_model_info()
# Ask user if they want to proceed with model testing
response = input("\nProceed with model testing? This will download models if not cached. (y/n): ")
if response.lower().startswith('y'):
test_local_models()
else:
print("Skipping model testing.")
print("\n✅ Test complete!") |