Create app.py

app.py

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+import numpy as np 
+import cv2
+import tensorflow as tf
+from tensorflow import keras
+from PIL import Image, ImageOps
+net = cv2.dnn.readNetFromCaffe('colorization_deploy_v2.prototxt','drive/MyDrive/Lab2market2023/colorization_release_v2.caffemodel')
+pts = np.load('pts_in_hull.npy')
+
+class8 = net.getLayerId("class8_ab")
+conv8 = net.getLayerId("conv8_313_rh")
+pts = pts.transpose().reshape(2,313,1,1)
+
+
+net.getLayer(class8).blobs = [pts.astype("float32")]
+net.getLayer(conv8).blobs = [np.full([1,313],2.606,dtype='float32')]
+
+def infer(original_image):
+  #image = cv2.imread('bw.jpg')
+  image = keras.preprocessing.image.img_to_array(original_image)
+  scaled = image.astype("float32")/255.0
+  lab = cv2.cvtColor(scaled,cv2.COLOR_BGR2LAB)
+  #cv2.imshow("image",lab)
+
+  resized = cv2.resize(lab,(224,224))
+  L = cv2.split(resized)[0]
+  L -= 50
+
+
+  net.setInput(cv2.dnn.blobFromImage(L))
+  ab = net.forward()[0, :, :, :].transpose((1,2,0))
+
+  ab = cv2.resize(ab, (image.shape[1],image.shape[0]))
+
+  L = cv2.split(lab)[0]
+  colorized = np.concatenate((L[:,:,np.newaxis], ab), axis=2)
+  colorized = cv2.cvtColor(colorized,cv2.COLOR_LAB2BGR)
+  colorized = np.clip(colorized,0,1)
+
+  colorized = (255 * colorized).astype("uint8")
+
+  cv2_imshow(image)
+  cv2_imshow(colorized)
+  color_coverted = cv2.cvtColor(colorized, cv2.COLOR_BGR2RGB)
+  colorized = Image.fromarray(color_coverted)
+  return colorized
+  cv2.waitKey(0)
+    import gradio as gr
+examples=['bw.jpg','blw.jpg','boy.jpg']
+iface = gr.Interface(
+    fn=infer,
+    title="Colourization",
+    description = "OpenCV implementation of Colorful Image Colorization paper presented in ECCV, 2016.  🌆🎆",
+    inputs=[gr.inputs.Image(label="image", type="pil")],
+    outputs="image",
+    examples=examples,
+    cache_examples=True,
+     article = "Authors: <a href=\"https://github.com/Uviveknarayan\">Vivek Narayan</a>, <a href=\"https://github.com/chiranjan-7\">Chiranjan</a>,<a href=\"https://github.com/GangaSrujan\">Srujan</a>,<a href=\"https://github.com/RohanPawar3399\">Rohan Pawar</a>,<a href=\"https://github.com/pavankarthik77\">Pavan Karthik</a>").launch(enable_queue=True)