Update app.py

app.py

@@ -10,7 +10,7 @@ LABELS = ['NORMAL', 'TUBERCULOSIS', 'PNEUMONIA', 'COVID19']
 
 def predict_input_image(img):
   try:
-      img = Image.open(BytesIO(base64.b64decode(img)))
+      img = Image.open(BytesIO(base64.b64decode(img))).convert('RGB').resize((128,128))
       img = np.array(img)
   except:
       pass
@@ -20,9 +20,6 @@ def predict_input_image(img):
   prediction=model.predict(img_4d)[0]
   return {LABELS[i]: float(prediction[i]) for i in range(4)}
 
-def k():
-  return gr.update(value=None)
-
 with gr.Blocks(title="Chest X-Ray Disease Classification", css="") as demo:
   with gr.Row():
     textmd = gr.Markdown('''
@@ -33,11 +30,9 @@ with gr.Blocks(title="Chest X-Ray Disease Classification", css="") as demo:
     with gr.Column(scale=1, min_width=600):
       image = gr.inputs.Image(shape=(128,128))
       with gr.Row():
-        clear_btn = gr.Button("Clear")
         submit_btn = gr.Button("Submit", elem_id="warningk", variant='primary')
     label = gr.outputs.Label(num_top_classes=4)
     
-    clear_btn.click(k, inputs=[], outputs=image)
     submit_btn.click(predict_input_image, inputs=image, outputs=label, api_name="prediction_place")
 
 demo.launch()