Deploying to HF

app.py

@@ -115,7 +115,13 @@ def create_model_from_checkpoint():
 model = create_model_from_checkpoint()
 labels = [ "benign", "malignant", "normal" ]
 
-def predict(img, shap_samples, shap_stdevs, occlusion_stride, occlusion_window):
+def predict(gr_inputs):
+    img = gr_inputs[0]
+    shap_samples = gr_inputs[1]
+    shap_stdevs = gr_inputs[2]
+    occlusion_stride = gr_inputs[3]
+    occlusion_window = gr_inputs[4]
+    
     explainer = Explainer(model, img, labels)
     return [explainer.confidences,
             explainer.shap(shap_samples, shap_stdevs),