raw output

app.py

@@ -6,7 +6,6 @@ from models.model import GLPDepth
 from PIL import Image
 from torchvision import transforms
 import matplotlib.pyplot as plt
-from matplotlib.backends.backend_agg import FigureCanvasAgg
 import numpy as np
 
 
@@ -48,16 +47,19 @@ def predict(input_image):
     data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
     data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
 
-    return data
+    return data, str(predicted_image.tolist())
 
 iface = gr.Interface(
     fn=predict, 
     inputs=gr.Image(shape=(512,512)), 
-    outputs=gr.Image(shape=(512,512)),
+    outputs=[
+        gr.Image(shape=(512,512)),
+        gr.outputs.Textbox(label='Raw output')
+    ],
     examples=[
         ["demo_imgs/fake.jpg"] # use real image
     ],
     title="DTM Estimation",
-    description="This demo predict a DTM..."
+    description="This demo predict a DTM using GLP Depth model. It will scale input image to 512x512 and at the end it will apply a colormap to better visualize the output."
 )
 iface.launch()