test

app.py

@@ -1,16 +1,24 @@
 import gradio as gr
 import numpy as np
 from PIL import Image
-import tempfile
 
 from mussel.utils import extract_features, segment_tissue
 
 def analyze_slide(slide_path, model_name="RESNET50"):
-    patch_h5_path = tempfile.NamedTemporaryFile(suffix=".h5").name
-    feature_h5_path = tempfile.NamedTemporaryFile(suffix=".h5").name
-    segment_tissue(slide_path, output_h5_path=patch_h5_path, patch_size=224)
-    #extract_features(patch_h5_path=patch_h5_path, slide_path=slide_path, model_type=model_name, use_gpu=False, output_h5_path=feature_h5_path)
-    return patch_h5_path
+    patch_h5_path = "patches.h5"
+    segment_tissue(
+        slide_path=slide_path,
+        output_h5_path=patch_h5_path,
+        patch_size=224)
+    feature_h5_path = "features.h5"
+    extract_features(
+        slide_path,
+        output_h5_path=feature_h5_path,
+        patch_h5_path=patch_h5_path,
+        model_type=model_name
+    )
+
+    return feature_h5_path
 
 with gr.Blocks() as demo:
     gr.Markdown("# Whole Slide Image Featurization & Inference")