Spaces:
Paused
Paused
feat(api): fast FastAPI app + model loader refactor; add mock mode for tests\n\n- Add pyproject + setuptools config and console entrypoint\n- Implement enhanced field extraction + MRZ heuristics\n- Add response builder with compatibility for legacy MRZ fields\n- New preprocessing pipeline for PDFs/images\n- HF Spaces GPU: cache ENV, optional flash-attn, configurable base image\n- Add Make targets for Spaces GPU and local CPU\n- Add httpx for TestClient; tests pass in mock mode\n- Remove embedded model files and legacy app/modules
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| #!/usr/bin/env python3 | |
| """Quick API Test Script | |
| A simple script to quickly test the deployed Dots.OCR API endpoint. | |
| """ | |
| import requests | |
| import json | |
| import sys | |
| from pathlib import Path | |
| def test_api(base_url="http://localhost:7860"): | |
| """Quick test of the API endpoint.""" | |
| print(f"🔍 Testing API at {base_url}") | |
| # Health check | |
| try: | |
| health_response = requests.get(f"{base_url}/health", timeout=10) | |
| health_response.raise_for_status() | |
| health_data = health_response.json() | |
| print(f"✅ Health check passed: {health_data}") | |
| except Exception as e: | |
| print(f"❌ Health check failed: {e}") | |
| return False | |
| # Test with front image | |
| front_image = Path(__file__).parent / "tom_id_card_front.jpg" | |
| if not front_image.exists(): | |
| print(f"❌ Test image not found: {front_image}") | |
| return False | |
| print(f"📸 Testing with {front_image.name}") | |
| try: | |
| with open(front_image, 'rb') as f: | |
| files = {'file': f} | |
| response = requests.post( | |
| f"{base_url}/v1/id/ocr", | |
| files=files, | |
| timeout=30 | |
| ) | |
| response.raise_for_status() | |
| result = response.json() | |
| print(f"✅ OCR test passed") | |
| print(f" Request ID: {result.get('request_id')}") | |
| print(f" Media type: {result.get('media_type')}") | |
| print(f" Processing time: {result.get('processing_time'):.2f}s") | |
| print(f" Detections: {len(result.get('detections', []))}") | |
| # Show extracted fields | |
| for i, detection in enumerate(result.get('detections', [])): | |
| fields = detection.get('extracted_fields', {}) | |
| field_count = len([f for f in fields.values() if f is not None]) | |
| print(f" Page {i+1}: {field_count} fields extracted") | |
| # Show some key fields | |
| key_fields = ['document_number', 'surname', 'given_names', 'nationality'] | |
| for field in key_fields: | |
| if field in fields and fields[field] is not None: | |
| value = fields[field].get('value', 'N/A') if isinstance(fields[field], dict) else str(fields[field]) | |
| confidence = fields[field].get('confidence', 'N/A') if isinstance(fields[field], dict) else 'N/A' | |
| print(f" {field}: {value} (confidence: {confidence})") | |
| return True | |
| except Exception as e: | |
| print(f"❌ OCR test failed: {e}") | |
| return False | |
| if __name__ == "__main__": | |
| base_url = sys.argv[1] if len(sys.argv) > 1 else "http://localhost:7860" | |
| success = test_api(base_url) | |
| sys.exit(0 if success else 1) | |