Update app.py

app.py

@@ -29,36 +29,38 @@ def resize_image(image):
 
 
 def process(image):
+    # 이미지가 numpy 배열인 경우에만 PIL.Image 객체로 변환
+    if isinstance(image, np.ndarray):
+        orig_image = Image.fromarray(image)
+    else:
+        # 이미 PIL.Image.Image 객체인 경우, 변환 없이 사용
+        orig_image = image
 
-    # prepare input
-    orig_image = Image.fromarray(image)
-    w,h = orig_im_size = orig_image.size
+    w, h = orig_im_size = orig_image.size
     image = resize_image(orig_image)
     im_np = np.array(image)
-    im_tensor = torch.tensor(im_np, dtype=torch.float32).permute(2,0,1)
-    im_tensor = torch.unsqueeze(im_tensor,0)
-    im_tensor = torch.divide(im_tensor,255.0)
-    im_tensor = normalize(im_tensor,[0.5,0.5,0.5],[1.0,1.0,1.0])
+    im_tensor = torch.tensor(im_np, dtype=torch.float32).permute(2, 0, 1)
+    im_tensor = torch.unsqueeze(im_tensor, 0)
+    im_tensor = torch.divide(im_tensor, 255.0)
+    im_tensor = normalize(im_tensor, [0.5, 0.5, 0.5], [1.0, 1.0, 1.0])
     if torch.cuda.is_available():
-        im_tensor=im_tensor.cuda()
+        im_tensor = im_tensor.cuda()
 
-    #inference
-    result=net(im_tensor)
+    # inference
+    result = net(im_tensor)
     # post process
-    result = torch.squeeze(F.interpolate(result[0][0], size=(h,w), mode='bilinear') ,0)
+    result = torch.squeeze(F.interpolate(result[0][0], size=(h, w), mode='bilinear'), 0)
     ma = torch.max(result)
     mi = torch.min(result)
-    result = (result-mi)/(ma-mi)    
+    result = (result - mi) / (ma - mi)
     # image to pil
-    im_array = (result*255).cpu().data.numpy().astype(np.uint8)
+    im_array = (result * 255).cpu().data.numpy().astype(np.uint8)
     pil_im = Image.fromarray(np.squeeze(im_array))
     # paste the mask on the original image
-    new_im = Image.new("RGBA", pil_im.size, (0,0,0,0))
+    new_im = Image.new("RGBA", pil_im.size, (0, 0, 0, 0))
     new_im.paste(orig_image, mask=pil_im)
-    # new_orig_image = orig_image.convert('RGBA')
 
     return new_im
-    # return [new_orig_image, new_im]
 
 def calculate_position(org_size, add_size, position):
     if position == "상단 좌측":