116 lines
3.2 KiB
Python
116 lines
3.2 KiB
Python
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import os
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from os.path import isfile, join
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import imutils as imutils
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import numpy as np
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import cv2
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import constant
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import mimetypes
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try:
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from cv2 import cv2
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finally:
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pass
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proto_file = "./model/colorization_deploy_v2.prototxt"
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model = "./model/colorization_release_v2.caffemodel"
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points_file = "./model/pts_in_hull.npy"
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network = cv2.dnn.readNetFromCaffe(proto_file, model)
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points = np.load(points_file)
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points = points.transpose().reshape(2, 313, 1, 1)
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class_layer = network.getLayerId("class8_ab")
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convolution_layer = network.getLayerId("conv8_313_rh")
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network.getLayer(class_layer).blobs = [points.astype(constant.FLOAT32)]
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network.getLayer(convolution_layer).blobs = [np.full([1, 313], 2.606, dtype=constant.FLOAT32)]
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# Convert from grayscale to gray to remove all little noises, and then again to rgb
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def clear_image(image):
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cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)
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return image
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def convert_frames_to_video(file_name):
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path_in = 'videos/colorized_frames/'
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path_out = 'videos/output/' + file_name.replace('/', '_')
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frame_array = []
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files = [f for f in os.listdir(path_in) if isfile(join(path_in, f))]
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files.sort(key=lambda x: int(x[5:-4]))
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for i in range(len(files)):
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filename = path_in + files[i]
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img = cv2.imread(filename)
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height, width, layers = img.shape
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size = (width, height)
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frame_array.append(img)
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out = cv2.VideoWriter(path_out, cv2.VideoWriter_fourcc(*'MJPG'), 30.0, size)
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for i in range(len(frame_array)):
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out.write(frame_array[i])
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out.release()
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def colorize_image(image):
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image_scaled = image.astype(constant.FLOAT32) / 255.0
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lab = cv2.cvtColor(image_scaled, cv2.COLOR_RGB2LAB)
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resized = cv2.resize(lab, (224, 224))
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image_l_channel = cv2.split(resized)[0] - 50
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network.setInput(cv2.dnn.blobFromImage(image_l_channel))
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ab = network.forward()[0, :, :, :].transpose((1, 2, 0))
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ab = cv2.resize(ab, (image.shape[1], image.shape[0]))
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image_l_channel = cv2.split(lab)[0]
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colorized = np.concatenate((image_l_channel[:, :, np.newaxis], ab), axis=2)
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colorized = cv2.cvtColor(colorized, cv2.COLOR_LAB2RGB)
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colorized = np.clip(colorized, 0, 1)
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return (255 * colorized).astype("uint8")
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def colorize(file_path: str) -> None:
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file_type = mimetypes.guess_type(file_path)[0].split('/')
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if file_type[0] == 'image':
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image = cv2.imread(file_path)
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colorized = colorize_image(image)
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cv2.imwrite("images/output/" + file_path.replace('/', '_'), cv2.cvtColor(colorized, cv2.COLOR_RGB2BGR))
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print('Success')
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elif file_type[0] == 'video':
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vs = cv2.VideoCapture(file_path)
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count = 0
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success = True
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while success:
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success, frame = vs.read()
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if frame is None:
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break
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frame = imutils.resize(frame, 500)
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colorized = colorize_image(frame)
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cv2.imwrite("./videos/colorized_frames/frame%d.jpg" % count, colorized)
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count += 1
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key = cv2.waitKey(1) & 0xFF
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if key == ord("q"):
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break
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vs.release()
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convert_frames_to_video(file_path)
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print('Success')
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else:
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print('Wrong media format')
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