Update app.py

app.py

@@ -5,18 +5,24 @@ from PIL import Image
 from cellpose import models
 
 
-def inference(img, model_path, **model_params):
-    inf_model = models.CellposeModel(gpu=False, pretrained_model=model_path)
-    preds, flows, _ = inf_model.eval([img], **model_params)
-    return preds, flows
+@st.cache()
+def load_model(model_path):
+    inf_model = models.CellposeModel(gpu=False, pretrained_model=model_path)    
+    return inf_model
+
+#def inference(img, model_path, **model_params):
+#    inf_model = models.CellposeModel(gpu=False, pretrained_model=model_path)
+#    preds, flows, _ = inf_model.eval([img], **model_params)
+#    return preds, flows
 
 
 if __name__ == "__main__":
 
     st.title("Sartorius Neuronal Cell Segmentation")
-
+    
+    inf_model = models.CellposeModel(gpu=False, pretrained_model=model_path)    
     uploaded_img = st.file_uploader(label="Upload neuronal cell image")
-
+    
     with st.expander("View input image"):
         if uploaded_img is not None:
             st.image(uploaded_img)
@@ -36,11 +42,12 @@ if __name__ == "__main__":
             "resample": True,
         }
         with st.spinner("Performing segmentation. This might take a while..."):
-            preds, flows = inference(
-                img=img,
-                model_path="./cellpose_residual_on_style_on_concatenation_off_fold1_ep_649_cv_0.2834",
-                **model_params
-            )
+            #preds, flows = inference(
+             #   img=img,
+              #  model_path="./cellpose_residual_on_style_on_concatenation_off_fold1_ep_649_cv_0.2834",
+               # **model_params
+            #)
+            preds, flows, _ = inf_model.eval([img], **model_params)
 
         fig, (ax1, ax2, ax3) = plt.subplots(1, 3)
         ax1.axis("off")