workflow stuff

runSDSdemo.py

@@ -92,20 +92,15 @@ def predict(input_img):
   # probabilities of all classes
   pred_softmax = torch.softmax(outputs, dim=1).cpu().numpy()[0]
   # class with hightest probability
-  pred = torch.argmax(outputs, dim=1).cpu().numpy()
   # diagnostic suggestions
-
-  # grad_cam image
-  target_layers = model.features[-1]
-  output_img = image_grad_cam(model,leasion_tensor,input_float_np,target_layers)
   # return label dict and suggestion
-  return {classes[i]: float(pred_softmax[i]) for i in range(len(classes))}, output_img
+  return {classes[i]: float(pred_softmax[i]) for i in range(len(classes))}
 
 # start gradio application
 gr.Interface(
         fn=predict, 
         inputs=gr.inputs.Image(), 
-        outputs=[gr.outputs.Label(label="Predict Result"), gr.outputs.Image(label="GradCAM")],
+        outputs=[gr.outputs.Label(label="Predict Result")],
         examples=[['images/video01_000014_prep.png'],['images/video01_001403.png'],['images/video01_001528_pack.png']],
         title="Surgical Workflow Classifier"
       ).launch()