Update app.py

app.py

@@ -9,6 +9,34 @@ from matplotlib.colors import hsv_to_rgb
 import cv2
 import gradio as gr
 
+
+def preprocess(image):
+    # Resize
+    ratio = 800.0 / min(image.size[0], image.size[1])
+    image = image.resize((int(ratio * image.size[0]), int(ratio * image.size[1])), Image.BILINEAR)
+
+    # Convert to BGR
+    image = np.array(image)[:, :, [2, 1, 0]].astype('float32')
+
+    # HWC -> CHW
+    image = np.transpose(image, [2, 0, 1])
+
+    # Normalize
+    mean_vec = np.array([102.9801, 115.9465, 122.7717])
+    for i in range(image.shape[0]):
+        image[i, :, :] = image[i, :, :] - mean_vec[i]
+
+    # Pad to be divisible of 32
+    import math
+    padded_h = int(math.ceil(image.shape[1] / 32) * 32)
+    padded_w = int(math.ceil(image.shape[2] / 32) * 32)
+
+    padded_image = np.zeros((3, padded_h, padded_w), dtype=np.float32)
+    padded_image[:, :image.shape[1], :image.shape[2]] = image
+    image = padded_image
+
+    return image
+
 preprocess = transforms.Compose([
     transforms.ToTensor(),
     transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),