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README.md

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+# Adaptive Compressed Sensing for Real-Time Video Compression, Transmission, and Reconstruction (DSAA'2023)
+
+In this repository we provide code of the paper:
+> **Adaptive Compressed Sensing for Real-Time Video Compression, Transmission, and Reconstruction**
+> 
+> Yaping Zhao, Qunsong Zeng, Edmund Y. Lam
+> 
+> paper link: https://ieeexplore.ieee.org/abstract/document/10302598
+
+<p align="right">
+  <img src="teaser.png" />
+</p>
+
+## Dataset
+The videos used in our experiments are available at [OneDrive](https://connecthkuhk-my.sharepoint.com/:u:/g/personal/zhaoyp_connect_hku_hk/EUiZDLQQxCFEmPHHeGf-sFIBjMAIfffMQN4KA_fbcQjceg?e=CsQVL8).
+
+Please extract `video.zip` to `video` folder.
+
+## Usage
+### Reproduce Paper Results
+#### Compression
+Simply run:
+```angular2html
+python main.py
+```
+Navigate to the `video` folder. You will see files `video*.mp4` as the original videos, and `meas*.mp4` as the compressed videos.
+#### Reconstruction
+In our paper, we adopt the classical [GAP-TV](https://ieeexplore.ieee.org/document/7532817) algorithm to reconstruct videos. 
+For higher reconstruction quality, we recommend [DEQSCI](https://github.com/IndigoPurple/DEQSCI).
+
+###Adjust the Compression Rate
+Modify the parameter `cr`, which is the compression rate, in Line 53 of the file `main.py`.
+
+```angular2html
+......
+### compress video frames into measurements
+
+    output_path = './video/meas%d.mp4' %i
+    img_num = len(os.listdir(folder_name))
+--> cr = 8 # compression rate
+    meas_num = img_num // cr
+......
+```
+
+## Citation
+Cite our paper if you find it interesting!
+
+```
+@INPROCEEDINGS{10302598,
+  author={Zhao, Yaping and Zeng, Qunsong and Lam, Edmund Y.},
+  booktitle={2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)}, 
+  title={Adaptive Compressed Sensing for Real-Time Video Compression, Transmission, and Reconstruction}, 
+  year={2023},
+  volume={},
+  number={},
+  pages={1-10},
+  doi={10.1109/DSAA60987.2023.10302598}}
+```

main.py

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+import numpy as np
+import cv2
+import os
+
+
+input_path = './video/'
+video_num = 4
+for i in range(1, video_num+1):
+    # decompose videos into frames
+
+    # Read the video from specified path
+    cam = cv2.VideoCapture("%svideo%d.mp4"%(input_path,i))
+    folder_name = './temp/img%d/'%i
+    try:
+        # creating a folder named data
+        if not os.path.exists(folder_name):
+            os.makedirs(folder_name)
+
+    # if not created then raise error
+    except OSError:
+        print('Error: Creating directory of data')
+
+    # frame
+    currentframe = 0
+
+    while (True):
+
+        # reading from frame
+        ret, frame = cam.read()
+
+        if ret:
+            # if video is still left continue creating images
+            name = './%sframe' % folder_name + str(currentframe) + '.png'
+            print('Creating...' + name)
+
+            # writing the extracted images
+            cv2.imwrite(name, frame)
+
+            # increasing counter so that it will
+            # show how many frames are created
+            currentframe += 1
+        else:
+            break
+
+    # Release all space and windows once done
+    cam.release()
+    cv2.destroyAllWindows()
+
+    ### compress video frames into measurements
+
+    output_path = './video/meas%d.mp4' %i
+    img_num = len(os.listdir(folder_name))
+    cr = 8 # compression rate
+    meas_num = img_num // cr
+    img = cv2.imread('%sframe1.png' % folder_name)
+    height, width, c = img.shape
+    meas = np.zeros((height, width, 3, meas_num))
+    mask = np.random.randint(2, size=(height, width, 3, cr))
+
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')  # *'mp4v'
+    video = cv2.VideoWriter(output_path, fourcc, 120, (width, height))
+
+    # imgs = []
+    print(meas_num)
+    for i in range(meas_num):  # meas_num
+        print(i)
+        # meas = np.zeros((height,width,3,cr))
+        meas_temp = np.zeros((height, width, 3))
+        for k in range(cr):
+            img = cv2.imread('%sframe%d.png' % (folder_name, i * cr + k))
+            # imgs.append(img)
+            for j in range(c):
+                meas_temp[:, :, j] += np.multiply(mask[:, :, j, k], img[:, :, j])
+        # meas[:, :, :,i] = meas_temp
+        img = np.uint8(meas_temp / cr)
+        img = cv2.cvtColor(img, cv2.COLOR_HSV2RGB)
+        video.write(img)
+
+    cv2.destroyAllWindows()
+    video.release()