Update app.py

app.py

@@ -1,20 +1,30 @@
 import gradio as gr
+import cv2
+import torch
 from mmdet.apis import init_detector, inference_detector
 import mmcv
+import numpy as np
 
-# Modellpfade
-config_file = 'configs/fashionformer/fashionpedia/fashionformer_r50_mlvl_feat_3x.py'
-checkpoint_file = 'checkpoints/fashionformer_r50.pth'
+# Model-Config & Checkpoint
+CONFIG_FILE = 'configs/fashionformer/fashionpedia/fashionformer_r50_mlvl_feat_3x.py'
+CHECKPOINT_FILE = 'checkpoints/fashionformer_r50_mlvl_feat_3x.pth'  # Pfad anpassen
 
 # Modell laden
-model = init_detector(config_file, checkpoint_file, device='cpu')
+model = init_detector(CONFIG_FILE, CHECKPOINT_FILE, device='cpu')
 
+# Inferenzfunktion
 def predict(image):
     result = inference_detector(model, image)
-    model.show_result(image, result, out_file='result.jpg', show=False)
-    return 'result.jpg'
+    img_out = model.show_result(image, result, out_file=None, show=False)
+    return img_out
 
-gr.Interface(fn=predict, 
-             inputs=gr.Image(type="filepath"), 
-             outputs="image", 
-             title="FashionFormer Segmentierung").launch()
+# 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."
+)
+
+demo.launch()