test_hf_space.py

#!/usr/bin/env python
"""Test HuggingFace Space API directly"""

import sys
import json
import tempfile
from PIL import Image

try:
    from gradio_client import Client, handle_file
except ImportError:
    print("❌ gradio_client not installed")
    sys.exit(1)

try:
    # Test image path
    test_image_path = r"C:\Users\barat\OneDrive\Desktop\test_image.jpg"
    
    print(f"Loading test image: {test_image_path}")
    image = Image.open(test_image_path)
    print(f"✅ Image loaded: {image.size}")
    
    # Connect to HF Space
    HF_SPACE_ID = "BARATH0070/plate-detector"
    print(f"\n🔌 Connecting to HF Space: {HF_SPACE_ID}")
    
    client = Client(HF_SPACE_ID)
    print("✅ Connected to HF Space")
    
    # View the API
    print("\n📋 Checking available endpoints...")
    try:
        info = client.view_api()
        print("Available API endpoints:")
        print(json.dumps(info, indent=2, default=str))
    except Exception as e:
        print(f"⚠️  Could not view API: {e}")
    
    # Save image to temp file
    print("\n📸 Saving image to temp file...")
    with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as tmp:
        image.save(tmp.name)
        tmp_path = tmp.name
        print(f"✅ Temp file: {tmp_path}")
    
    # Try to call the API
    print("\n🚀 Calling HF Space API...")
    image_input = handle_file(tmp_path)
    print(f"✅ Image input prepared: {image_input}")
    
    # Try different endpoint names
    endpoints = [
        "/detect_and_save",
        "/predict_0",
        "/predict",
        "/run",
    ]
    
    for endpoint in endpoints:
        try:
            print(f"\n  Trying endpoint: {endpoint}")
            result = client.predict(image_input, api_name=endpoint)
            print(f"  ✅ Success! Result type: {type(result)}")
            print(f"  Result: {result}")
            
            # Try to parse as JSON if it's a string
            if isinstance(result, (list, tuple)):
                print(f"  Result length: {len(result)}")
                for i, item in enumerate(result):
                    print(f"    [{i}] type={type(item).__name__}, value={item}")
            
            break
        except Exception as e:
            print(f"  ⚠️  Failed: {e}")
    
    # Cleanup
    import os
    if os.path.exists(tmp_path):
        os.remove(tmp_path)
        print(f"\n✅ Cleaned up temp file")

except Exception as e:
    print(f"❌ Error: {e}")
    import traceback
    traceback.print_exc()