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| """Gradio Blocks UI: image / video / webcam tabs plus a JSON API endpoint.""" | |
| import gradio as gr | |
| from src.configs import settings | |
| from src.inference.predictor import Predictor | |
| from src.inference.video import annotate_video | |
| def _predict_image(predictor: Predictor, image): | |
| if image is None: | |
| return None, "No image provided", "N/A" | |
| result = predictor.classify(image) | |
| return result.annotated_frame, result.label, result.confidence_str | |
| def _predict_api(predictor: Predictor, image): | |
| if image is None: | |
| return {"success": False, "error": "No image provided"} | |
| try: | |
| result = predictor.classify(image) | |
| return { | |
| "success": True, | |
| "class": result.label, | |
| "confidence": result.confidence_str, | |
| "confidence_value": result.confidence, | |
| "threshold_exceeded": result.threshold_exceeded, | |
| } | |
| except Exception as exc: | |
| return {"success": False, "error": str(exc)} | |
| def _predict_video(predictor: Predictor, video_path): | |
| if video_path is None: | |
| return None | |
| return annotate_video(video_path, predictor) | |
| def build_interface(predictor: Predictor) -> gr.Blocks: | |
| with gr.Blocks(title="SerraSafe - Détection de Pestes") as demo: | |
| gr.Markdown( | |
| f""" | |
| # 🌱 SerraSafe Guardian - Système de Détection de Pestes | |
| Ce système utilise l'intelligence artificielle pour détecter et classifier les pestes dans votre serre. | |
| **Classes détectées:** {", ".join(settings.CLASS_LABELS)} | |
| """ | |
| ) | |
| with gr.Tab("📷 Analyse Image"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| image_input = gr.Image(type="numpy", label="Télécharger une image") | |
| image_button = gr.Button("Analyser l'image", variant="primary") | |
| with gr.Column(): | |
| image_output = gr.Image(label="Résultat") | |
| image_label = gr.Textbox(label="Classe détectée") | |
| image_confidence = gr.Textbox(label="Confiance") | |
| image_button.click( | |
| fn=lambda img: _predict_image(predictor, img), | |
| inputs=image_input, | |
| outputs=[image_output, image_label, image_confidence], | |
| ) | |
| with gr.Tab("📹 Analyse Vidéo"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| video_input = gr.Video(label="Télécharger une vidéo") | |
| video_button = gr.Button("Analyser la vidéo", variant="primary") | |
| with gr.Column(): | |
| video_output = gr.Video(label="Vidéo annotée") | |
| video_button.click( | |
| fn=lambda path: _predict_video(predictor, path), | |
| inputs=video_input, | |
| outputs=video_output, | |
| ) | |
| with gr.Tab("🎥 Webcam"): | |
| gr.Markdown("### Capturez une image avec votre webcam pour l'analyser") | |
| with gr.Row(): | |
| with gr.Column(): | |
| webcam_input = gr.Image(sources=["webcam"], type="numpy", label="Webcam", streaming=False) | |
| webcam_button = gr.Button("Analyser", variant="primary") | |
| with gr.Column(): | |
| webcam_output = gr.Image(label="Résultat") | |
| webcam_label = gr.Textbox(label="Classe détectée") | |
| webcam_confidence = gr.Textbox(label="Confiance") | |
| webcam_button.click( | |
| fn=lambda img: _predict_image(predictor, img), | |
| inputs=webcam_input, | |
| outputs=[webcam_output, webcam_label, webcam_confidence], | |
| ) | |
| with gr.Tab("🔌 API (JSON)"): | |
| gr.Markdown( | |
| """ | |
| ### API pour clients externes | |
| Utilisez cet endpoint pour obtenir des prédictions en JSON. | |
| **Endpoint:** `/api/predict` (POST, retourne `class`, `confidence`, `threshold_exceeded`) | |
| """ | |
| ) | |
| with gr.Column(): | |
| api_image_input = gr.Image(type="numpy", label="Image") | |
| api_button = gr.Button("Tester l'API", variant="primary") | |
| api_output = gr.JSON(label="Réponse JSON") | |
| api_button.click( | |
| fn=lambda img: _predict_api(predictor, img), | |
| inputs=api_image_input, | |
| outputs=api_output, | |
| api_name="predict", | |
| ) | |
| return demo | |