Update app.py

app.py

@@ -1,5 +1,14 @@
 import gradio as gr
+import PIL
+from PIL import Image
+import numpy as np
+import os
+import uuid
+import torch
+from torch import autocast
+import cv2
 
+'''
 from io import BytesIO
 import requests
 import PIL
@@ -98,11 +107,11 @@ def preprocess_mask(mask):
     
 def model_process(init_image, mask):
     global model
-    '''
-    input = request.files
+    
+    # input = request.files
     # RGB
-    origin_image_bytes = input["image"].read()
-    '''
+    # origin_image_bytes = input["image"].read()
+    
     
     print(f'liuyz_2_here_')
     
@@ -111,9 +120,9 @@ def model_process(init_image, mask):
     original_shape = init_image.shape
     interpolation = cv2.INTER_CUBIC
     
-    '''
-    form = request.form
-    '''
+    
+    # form = request.form
+    
     size_limit = 1080 # : Union[int, str] = form.get("sizeLimit", "1080")
     if size_limit == "Original":
         size_limit = max(image.shape)
@@ -173,16 +182,6 @@ def model_process(init_image, mask):
 
     ext = get_image_ext(origin_image_bytes)
     return ext
-    '''
-    response = make_response(
-        send_file(
-            io.BytesIO(numpy_to_bytes(res_np_img, ext)),
-            mimetype=f"image/{ext}",
-        )
-    )
-    response.headers["X-Seed"] = str(config.sd_seed)
-    return response
-    '''
     
 model = ModelManager(
         name='lama',
@@ -193,7 +192,7 @@ model = ModelManager(
         # sd_run_local=True,
         # callback=diffuser_callback,
     )
-    
+'''    
 
 '''
 pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-inpainting", dtype=torch.float16, revision="fp16", use_auth_token=auth_token).to(device)