Update app.py

app.py

@@ -1,30 +1,15 @@
-import gradio as gr
-import cv2
-import torch
 from mmdet.apis import init_detector, inference_detector
 import mmcv
-import numpy as np
-
-# Model-Config & Checkpoint
-CONFIG_FILE = 'configs/fashionformer/fashionpedia/fashionformer_r50_mlvl_feat_3x.py'
-CHECKPOINT_FILE = 'checkpoints/fashionformer_r50_3x.pth'  # Pfad anpassen
+import gradio as gr
 
-# Modell laden
-model = init_detector(CONFIG_FILE, CHECKPOINT_FILE, device='cpu')
+config_file = 'config/fashionformer_fashionpedia.py'
+checkpoint_file = 'checkpoints/fashionformer.pth'
 
-# Inferenzfunktion
-def predict(image):
-    result = inference_detector(model, image)
-    img_out = model.show_result(image, result, out_file=None, show=False)
-    return img_out
+model = init_detector(config_file, checkpoint_file, device='cpu')
 
-# Gradio UI
-demo = gr.Interface(
-    fn=predict,
-    inputs=gr.Image(type="filepath", label="Bild hochladen"),
-    outputs=gr.Image(type="numpy", label="Segmentiertes Ergebnis"),
-    title="FashionFormer – Mode-Segmentierung",
-    description="Dieses Tool erkennt und segmentiert Kleidungsstücke auf Bildern mithilfe des FashionFormer-Modells."
-)
+def predict(img):
+    result = inference_detector(model, img)
+    model.show_result(img, result, out_file='result.jpg', show=False)
+    return 'result.jpg'
 
-demo.launch()
+gr.Interface(fn=predict, inputs=gr.Image(type="filepath"), outputs="image").launch()