Methodology:
• Library Used: Open CV
• Framework Used: Flask (Programming Languages Used: HTML, Python, CSS)
• For Edit Page: Brightness: To increase brightness, we added some values to each channel and brightness was increased.
Contrast: Mid tones are eliminated. Image will contain higher number of dark/blacks and whites/highlights.
Blur: We used normal open cv blur function which is average blurring.
Sharpen: we used kernel or convolution matrix for sharping image For max: [[-1,-1,-1], [-1, 9,-1],[-1,-1,-1]] For min: [[0,-1,0], [-1,5,-1], [0,-1,0]]
Denoise: Performed image denoising using Non-local Means Denoising algorithm with several computational optimizations. Noise expected to be a gaussian white noise.
Rotate: rotate() method is used to rotate a 2D array in multiples of 90 degrees.
Resize: We used cv2.resize() which reduces the number of pixels from an image.
Filters: We implemented several filters like Color-pop, cool, etc. by using different methods.
• For Nightmode Page: We implemented a night-mode feature which aims to utilise a dual channel prior-based method for low illumination image enhancement with a single image. Taking the dark channel into consideration removes block effects in some regions and helps see various details from dark images clearly.
• For Live Effects Page: We implemented 12 live filters using OpenCV we got the frame feed from user webcam then we used haarcascade to recognize frontal facial features and then attached PNG files (clip arts like sunglasses, moustache, ipl team bands, etc.) on various facial positions.
• Link to test project live on web: https://kubergupta.pythonanywhere.com/ (Note: The live effects page is not supported on web deployed link because of constraints in the webcam access due to security issues. The live effects page is supported on Local Machine only.)