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: Vivek Narayan, Chiranjan,Srujan,Rohan Pawar,Pavan Karthik").launch(enable_queue=True)