tanyar09
ef7a296a9b
This commit finalizes the migration from face_recognition to DeepFace across all phases. It includes updates to the database schema, core processing, GUI integration, and comprehensive testing. All features are now powered by DeepFace technology, providing superior accuracy and enhanced metadata handling. The README and documentation have been updated to reflect these changes, ensuring clarity on the new capabilities and production readiness of the PunimTag system. All tests are passing, confirming the successful integration.
72 lines
2.3 KiB
Python
Executable File
72 lines
2.3 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Launcher script for PunimTag Dashboard
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Adds project root to Python path and launches the dashboard
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"""
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import os
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import sys
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import warnings
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from pathlib import Path
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# Suppress TensorFlow warnings (must be before DeepFace import)
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os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
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warnings.filterwarnings('ignore')
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# Add project root to Python path
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project_root = Path(__file__).parent
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sys.path.insert(0, str(project_root))
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# Now import required modules
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from src.gui.dashboard_gui import DashboardGUI
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from src.gui.gui_core import GUICore
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from src.core.database import DatabaseManager
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from src.core.face_processing import FaceProcessor
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from src.core.photo_management import PhotoManager
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from src.core.tag_management import TagManager
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from src.core.search_stats import SearchStats
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from src.core.config import DEFAULT_DB_PATH
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if __name__ == "__main__":
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# Initialize all required components
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gui_core = GUICore()
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db_manager = DatabaseManager(DEFAULT_DB_PATH, verbose=0)
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# Initialize face_processor without detector/model (will be updated by GUI)
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face_processor = FaceProcessor(db_manager, verbose=0)
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photo_manager = PhotoManager(db_manager, verbose=0)
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tag_manager = TagManager(db_manager, verbose=0)
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search_stats = SearchStats(db_manager)
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# Define callback functions for scan and process operations
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def on_scan(folder, recursive):
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"""Callback for scanning photos"""
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return photo_manager.scan_folder(folder, recursive)
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def on_process(limit=None, stop_event=None, progress_callback=None,
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detector_backend=None, model_name=None):
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"""Callback for processing faces with DeepFace settings"""
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# Update face_processor settings if provided
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if detector_backend:
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face_processor.detector_backend = detector_backend
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if model_name:
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face_processor.model_name = model_name
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return face_processor.process_faces(
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limit=limit or 50,
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stop_event=stop_event,
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progress_callback=progress_callback
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)
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# Create and run dashboard
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app = DashboardGUI(
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gui_core=gui_core,
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db_manager=db_manager,
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face_processor=face_processor,
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on_scan=on_scan,
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on_process=on_process,
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search_stats=search_stats,
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tag_manager=tag_manager
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)
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app.open()
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