convert pil image to cv2?

app.py

@@ -17,9 +17,17 @@ output_layer = compiled_model.output(0)
 #Inference
 ##### 
 def predict(img):
-    #img = PILImage.create(img)
-    #pred,pred_idx,probs = learn.predict(img)
-    #return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+    # https://stackoverflow.com/a/32264327
+    image = cv2.cvtColor(numpy.array(img), cv2.COLOR_BGR2RGB)
+    
+    # The MobileNet model expects images in RGB format.
+    #image = cv2.cvtColor(cv2.imread(img), code=cv2.COLOR_BGR2RGB)
+    # Resize to MobileNet image shape.
+    input_image = cv2.resize(src=image, dsize=(224, 224))
+    # Reshape to model input shape.
+    input_image = np.expand_dims(input_image, 0)
+   
     
     # TODO: get n best results with corresponding probabilities?
     
@@ -47,7 +55,7 @@ enable_queue=True
 
 gr.Interface(
     fn=predict,
-    inputs=gr.inputs.Image(shape=(512, 512)),
+    inputs=gr.inputs.Image(),
     outputs=gr.outputs.Label(num_top_classes=1),
     title=title,
     description=description,