video colourization

Video Colourization/(88) Black and White Old Songs into Colorful Videos - YouTube.url

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+[InternetShortcut]
+URL=https://www.youtube.com/playlist?list=PLyeWzbpbicN032fYAmjBoxPQn9AlB1uwl

Video Colourization/README.md

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+
+# `Video_colorization`.[py](https://github.com/imvickykumar999/Video-Colorization/blob/main/video_colorization.py)
+
+    pip install -r requirements.txt
+
+-----------------
+
+## `Uploaded` [`PlayList`](https://www.youtube.com/playlist?list=PLyeWzbpbicN032fYAmjBoxPQn9AlB1uwl)
+
+- [Beqaraar Karake Hamen Yun Na Jaaiye](https://youtu.be/r4cJrr0WczE) **(32.4k+ views)**
+- [Mera Joota Hai Japani](https://www.youtube.com/shorts/FlktPZTxCq4)
+- [Haal Kaisa Hai Janaab Ka](https://youtu.be/dRTmhoUrr_0) **(7.4k+ views)**
+- [Itna Na Mujhse Tu Pyaar Badha](https://www.youtube.com/watch?v=AFy573PU8Og)
+- [Aa chal ke tujhe main leke chaloon](https://www.youtube.com/watch?v=gqDkgqpBrwo)
+
+--------------------------------
+
+## `Transformed Video`
+
+https://user-images.githubusercontent.com/50515418/208450925-81a28039-1ee6-48e6-afc4-e41ebb9ab95c.mp4
+
+### `It took 20 minutes to transform only 10 seconds video.`
+
+## `Original Video`
+
+https://user-images.githubusercontent.com/50515418/208451041-b5ab039c-36d4-432f-9047-f15d3da0bea9.mp4
+
+----------------------
+
+**Clone the repository; install dependencies**
+
+```
+gh repo clone imvickykumar999/Video-Colorization
+pip install requirements.txt
+```
+
+**Colorize!** This script will colorize an image. The results should match the images in the `imgs_out` folder.
+
+```
+python demo_release.py -i imgs/output.jpg
+```
+
+**Model loading in Python** The following loads pretrained colorizers. See [demo_release.py](https://github.com/imvickykumar999/Video-Colorization/blob/main/extras/demo_release.py) for some details on how to run the model. There are some pre and post-processing steps: convert to Lab space, resize to 256x256, colorize, and concatenate to the original full resolution, and convert to RGB.
+
+```python
+import colorizers
+colorizer_eccv16 = colorizers.eccv16().eval()
+colorizer_siggraph17 = colorizers.siggraph17().eval()
+```
+
+--------------------
+
+### Original implementation (Caffe branch)
+
+https://pub.towardsai.net/colorizing-images-with-deep-learning-a34d11587643
+
+The original implementation contained train and testing, our network and AlexNet (for representation learning tests), as well as representation learning tests. It is in Caffe and is no longer supported. Please see the [caffe](https://github.com/richzhang/colorization/tree/caffe) branch for it.
+
+### Citation ###
+
+If you find these models useful for your resesarch, please cite with these bibtexs.
+
+```
+@inproceedings{zhang2016colorful,
+  title={Colorful Image Colorization},
+  author={Zhang, Richard and Isola, Phillip and Efros, Alexei A},
+  booktitle={ECCV},
+  year={2016}
+}
+
+@article{zhang2017real,
+  title={Real-Time User-Guided Image Colorization with Learned Deep Priors},
+  author={Zhang, Richard and Zhu, Jun-Yan and Isola, Phillip and Geng, Xinyang and Lin, Angela S and Yu, Tianhe and Efros, Alexei A},
+  journal={ACM Transactions on Graphics (TOG)},
+  volume={9},
+  number={4},
+  year={2017},
+  publisher={ACM}
+}
+```
+
+----------------------------------
+
+## `Input command` in [Curl Commands Online](https://reqbin.com/curl)
+
+    curl \
+        -F 'image=https://keyassets.timeincuk.net/inspirewp/live/wp-content/uploads/sites/12/2019/01/BW-using-curves.jpg' \
+        -H 'api-key:c34c7088-11a1-456b-9a77-1384500eb46f' \
+        https://api.deepai.org/api/colorizer 
+
+-----------------------
+
+## `Output Response` : [deepai.org](https://deepai.org/machine-learning-model/colorizer) need payment of 5 doller per month.
+`I avoid such websites which need payments, this repository can do same for free.`
+
+    {
+        "status": "Out of API credits - please enter payment info in your dashboard: https://deepai.org/dashboard"
+    }
+
+---------------------------
+
+## `Output Video` on : [YouTube](https://youtube.com/shorts/FlktPZTxCq4?feature=share)
+
+![image](https://user-images.githubusercontent.com/50515418/208730165-93c8807d-8cf7-4626-827d-eaf191b71e06.png)

Video Colourization/requirements.txt

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+torch
+scikit-image
+numpy>=1.16.5,<1.23.0
+matplotlib
+argparse
+Pillow
+torchvision

Video Colourization/video_colorization.py

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+
+from moviepy.editor import VideoFileClip, AudioFileClip
+import moviepy.video.fx.all as vfx
+import argparse, os, cv2, shutil
+import matplotlib.pyplot as plt
+from colorizers import *
+from PIL import Image
+
+def step1():
+	try:
+		shutil.rmtree('vid_out')
+	except:
+		pass
+
+	try:
+		os.mkdir('vid_out')
+	except:
+		pass
+
+	try:
+		os.mkdir('vid')
+	except:
+		pass
+
+	file_name = 'vid/oldsong.mp4'
+	vidcap = cv2.VideoCapture(file_name)
+	success,image = vidcap.read()
+	count = 0
+
+	while success:
+		cv2.imwrite(f"vid_out/{str(count).zfill(6)}.jpg", image)     # save frame as JPEG file      
+		success,image = vidcap.read()
+		print(f'Read {count+1} frame: ', success)
+		count += 1
+
+def step2():
+	try:
+		shutil.rmtree('bw_vid_out')
+	except:
+		pass
+
+	try:
+		os.mkdir('bw_vid_out')
+	except:
+		pass
+
+	def magic(input_path, output_path):
+		parser = argparse.ArgumentParser()
+		parser.add_argument('--use_gpu', action='store_true', help='whether to use GPU')
+		opt = parser.parse_args()
+
+		colorizer_eccv16 = eccv16(pretrained=True).eval()
+		colorizer_siggraph17 = siggraph17(pretrained=True).eval()
+		if(opt.use_gpu):
+			colorizer_eccv16.cuda()
+			colorizer_siggraph17.cuda()
+
+		img = load_img(input_path)
+		(tens_l_orig, tens_l_rs) = preprocess_img(img, HW=(256,256))
+		if(opt.use_gpu):
+			tens_l_rs = tens_l_rs.cuda()
+
+		img_bw = postprocess_tens(tens_l_orig, torch.cat((0*tens_l_orig,0*tens_l_orig), dim=1))
+		out_img_eccv16 = postprocess_tens(tens_l_orig, colorizer_eccv16(tens_l_rs).cpu())
+		plt.imsave(output_path, out_img_eccv16)
+
+	images = [img for img in os.listdir('vid_out')
+				if img.endswith(".jpg") or
+					img.endswith(".jpeg") or
+					img.endswith("png")]
+
+	for i in images:
+		print('Processing for frame : ', i)
+		magic(f'vid_out/{i}', f'bw_vid_out/{i}')
+
+def step3():
+	mean_height = 0
+	mean_width = 0
+
+	path = 'bw_vid_out'
+	num_of_images = len(os.listdir('bw_vid_out'))
+	print(f'num_of_images = {num_of_images}')
+
+	for file in os.listdir('bw_vid_out'):
+		im = Image.open(os.path.join(path, file))
+		width, height = im.size
+		mean_width += width
+		mean_height += height
+
+	mean_width = int(mean_width / num_of_images)
+	mean_height = int(mean_height / num_of_images)
+
+	for file in os.listdir('bw_vid_out'):
+		if file.endswith(".jpg") or file.endswith(".jpeg") or file.endswith("png"):
+			im = Image.open(os.path.join(path, file))
+
+			width, height = im.size
+			imResize = im.resize((mean_width, mean_height), Image.Resampling.LANCZOS)
+			imResize.save(os.path.join(path, file), 'JPEG', quality = 95)
+			print(im.filename.split('\\')[-1], " is resized")
+
+	def generate_video():
+		image_folder = 'bw_vid_out'
+		video_name = 'mygeneratedvideo.avi'
+
+		images = [img for img in os.listdir(image_folder)
+				if img.endswith(".jpg") or
+					img.endswith(".jpeg") or
+					img.endswith("png")]
+
+		frame = cv2.imread(os.path.join(image_folder, images[0]))
+		height, width, layers = frame.shape
+		video = cv2.VideoWriter(os.path.join('vid', video_name), 0, 1, (width, height))
+
+		for image in images:
+			print('Writing for ', image)
+			video.write(cv2.imread(os.path.join(image_folder, image)))
+
+		cv2.destroyAllWindows()
+		video.release()
+
+	generate_video()
+
+def step4():
+	in_loc = 'vid/mygeneratedvideo.avi'
+	out_loc = 'vid/coloured.mp4'
+
+	clip = VideoFileClip(in_loc)
+	clip = clip.set_fps(clip.fps * 30)
+	final = clip.fx(vfx.speedx, 30)
+
+	audioclip = AudioFileClip("vid/oldsong.mp4")
+	videoclip = final.set_audio(audioclip)
+	videoclip.write_videofile(out_loc)
+
+step1()
+step2()
+step3()
+step4()