working on the app

app/app_savta.py

@@ -1,5 +1,7 @@
 import numpy as np
-
+import torch
+import sys
+from fastai.vision.all import *
 import gradio as gr
 
 title = "SavtaDepth WebApp"
@@ -12,7 +14,8 @@ examples = [
 ]
 favicon = "examples/favicon.ico"
 thumbnail = "examples/SavtaDepth.png"
-
+learner = unet_learner(resnet34, path='src/')
+learner.load('model')
 def sepia(input_img):
     sepia_filter = np.array(
         [[0.393, 0.769, 0.189], [0.349, 0.686, 0.168], [0.272, 0.534, 0.131]]
@@ -21,8 +24,10 @@ def sepia(input_img):
     sepia_img /= sepia_img.max()
     return sepia_img
 
+
+
 def main():
-	iface = gr.Interface(sepia, gr.inputs.Image(shape=(200, 200)), "image", title = title, description = description, article = article, examples = examples,theme ="peach",thumbnail=thumbnail)
+	iface = gr.Interface(sepia, gr.inputs.Image(shape=(640,480)), "image", title = title, description = description, article = article, examples = examples,theme ="peach",thumbnail=thumbnail)
 
 	iface.launch(favicon_path=favicon,auth=("admin", "dagshubsota123"),server_name="0.0.0.0")
 # enable_queue=True,auth=("admin", "pass1234")