Update app.py

app.py

@@ -52,8 +52,7 @@ def dice_coef(y_true, y_pred, smooth=1):
 # Load the model
 seg_model = tf.keras.models.load_model('seg_unet_model.h5', custom_objects={'Combo_loss': Combo_loss, 'dice_coef': dice_coef})
 
-# inputs = gr.inputs.Image(type="numpy", label="Upload an image", source="upload")
-inputs = gr.inputs.ImageUpload()
+inputs = gr.inputs.Image(type="pil", label="Upload an image", source="upload")
 image_output = gr.outputs.Image(type="numpy", label="Output Image")
 # outputs = gr.outputs.HTML() #uncomment for single class output 
 
@@ -67,7 +66,7 @@ def gen_pred(img=inputs, model=seg_model):
     img = tf.expand_dims(img, axis=0)
     pred = model.predict(img)
     pred = np.squeeze(pred, axis=0)
-    return pred
+    return "IN PROGRESS..."
 
 
 title = "<h1 style='text-align: center;'>Semantic Segmentation</h1>"
@@ -76,7 +75,7 @@ description = "Upload an image and get prediction mask"
 
 gr.Interface(fn=gen_pred, 
              inputs=inputs, 
-             outputs=image_output, 
+             outputs='text', 
              title=title, 
              examples=[["003e2c95d.jpg"], ["003b50a15.jpg"], ["003b48a9e.jpg"], ["0038cbe45.jpg"], ["00371aa92.jpg"]],
              # css=css_code,