Update app.py

app.py

@@ -78,6 +78,37 @@ def brush_stroke_mask(img, color=(255,255,255)):
     mask = generate_mask(height, width, img)
     return mask
 
+def image_resize(image, width = None, height = None, inter = cv2.INTER_AREA):
+    # initialize the dimensions of the image to be resized and
+    # grab the image size
+    dim = None
+    (h, w) = image.shape[:2]
+
+    # if both the width and height are None, then return the
+    # original image
+    if width is None and height is None:
+        return image
+
+    # check to see if the width is None
+    if width is None:
+        # calculate the ratio of the height and construct the
+        # dimensions
+        r = height / float(h)
+        dim = (int(w * r), height)
+
+    # otherwise, the height is None
+    else:
+        # calculate the ratio of the width and construct the
+        # dimensions
+        r = width / float(w)
+        dim = (width, int(h * r))
+
+    # resize the image
+    resized = cv2.resize(image, dim, interpolation = inter)
+
+    # return the resized image
+    return resized
+
 def inference(file, mode):
 
     im = cv2.imread(file, cv2.IMREAD_COLOR)
@@ -101,12 +132,11 @@ def inference(file, mode):
         return os.path.join("output.png")
     elif mode == "inpainting":
         im1 = cv2.imread(file, cv2.IMREAD_COLOR)
-        im2 = imutils.resize(im1, width=2048)
-        im3 = cv2.resize(im2, (0,0), fx=3, fy=3)
+        im2 = image_resize(im1, width = 1024)
         model = {'name':'GPEN-Inpainting-1024', 'size':1024}
         faceinpainter = FaceInpainting(size=model['size'], model=model['name'], channel_multiplier=2, device='cpu')
-        im = np.asarray(brush_stroke_mask(Image.fromarray(im3)))
-        inpaint = faceinpainter.process(im3)
+        im = np.asarray(brush_stroke_mask(Image.fromarray(im2)))
+        inpaint = faceinpainter.process(im2)
 
         cv2.imwrite(os.path.join("output.png"), inpaint)
         return os.path.join("output.png")