Update run.py

run.py

@@ -1,101 +1,18 @@
-import os
 import gradio as gr
-import cv2
-import numpy as np
-from insightface.app import FaceAnalysis
-import tempfile
-from moviepy.editor import VideoFileClip
 
-# ===== Configuration précoce pour éviter les erreurs =====
+# Fonction de test (remplacez-la par votre logique plus tard)
+def greet(name):
+    return f"Bonjour {name} !"
 
-os.environ["NO_ALBUMENTATIONS_UPDATE"] = "1"
-
-# Rediriger les chemins problématiques
-os.environ['MPLCONFIGDIR'] = '/tmp/matplotlib'
-os.environ['FONTCONFIG_PATH'] = '/tmp/fontconfig'
-
-os.makedirs('/tmp/matplotlib', exist_ok=True)
-os.makedirs('/tmp/fontconfig', exist_ok=True)
-
-# Forcer InsightFace à utiliser un répertoire accessible
-os.environ['INSIGHTFACE_ROOT'] = '/tmp/.insightface'
-os.environ["ORT_DISABLE_CUDA"] = "1"  # Désactiver CUDA si GPU indisponible
-
-def swap_face(source_face, target_face, frame):
-    src_emb = source_face.normed_embedding
-    tgt_bbox = target_face.bbox.astype(int)
-    resized_face = cv2.resize(source_face.img, (tgt_bbox[2]-tgt_bbox[0], tgt_bbox[3]-tgt_bbox[1]))
-    
-    mask = np.zeros_like(resized_face)
-    center = (mask.shape[1]//2, mask.shape[0]//2)
-    radius = int(min(mask.shape) * 0.45)
-    cv2.circle(mask, center, radius, (255,255,255), -1)
-    mask = cv2.GaussianBlur(mask, (15,15), 5)
-    
-    center = ((tgt_bbox[0]+tgt_bbox[2])//2, (tgt_bbox[1]+tgt_bbox[3])//2)
-    result = cv2.seamlessClone(resized_face, frame, mask, center, cv2.NORMAL_CLONE)
-    return result
-
-
-def process_video(source_img, target_video):
-    try:
-        face_app = FaceAnalysis(name="buffalo_l", root="/tmp/.insightface")
-        face_app.prepare(ctx_id=0, det_size=(640, 640))
-
-        source_faces = face_app.get(source_img)
-        if not source_faces:
-            raise ValueError("Aucun visage trouvé dans l'image source.")
-        source_face = source_faces[0]
-
-        temp_output = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
-
-        cap = cv2.VideoCapture(target_video)
-        fps = cap.get(cv2.CAP_PROP_FPS)
-        frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-        frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-
-        fourcc = cv2.VideoWriter_fourcc(*'avc1')
-        out = cv2.VideoWriter(temp_output.name, fourcc, fps, (frame_width, frame_height))
-
-        while True:
-            ret, frame = cap.read()
-            if not ret:
-                break
-
-            target_faces = face_app.get(frame)
-            for face in target_faces:
-                frame = swap_face(source_face, face, frame)
-
-            out.write(frame)
-
-        cap.release()
-        out.release()
-
-        # Réencodage final pour compatibilité Gradio
-        clip = VideoFileClip(temp_output.name)
-        final_path = tempfile.mktemp(suffix=".mp4")
-        clip.write_videofile(final_path, codec="libx264", audio_codec="aac", verbose=False, logger=None)
-
-        return final_path
-
-    except Exception as e:
-        print(f"Erreur : {str(e)}")
-        return None
-
-
-# Interface Gradio
+# Interface Gradio minimale
 demo = gr.Interface(
-    fn=process_video,
-    inputs=[
-        gr.Image(label="Visage Source", type="numpy"),
-        gr.Video(label="Vidéo Cible"),
-    ],
-    outputs=gr.Video(label="Vidéo Résultat"),
-    title="🎬 FaceSwap Pro",
-    description="Échangez des visages dans une vidéo.",
+    fn=greet,
+    inputs=gr.Textbox(label="Votre nom"),
+    outputs=gr.Textbox(label="Résultat"),
+    title="🧪 Test API Gradio",
+    description="Testez cette interface pour vérifier que l'API est bien trouvée.",
     allow_flagging="never"
 )
 
-
 if __name__ == "__main__":
     demo.launch(share=True)