Photographic Mosaic is, as the name suggests, is a python program that takes in a dataset of images and concatenates them to create a photographic mosaic (an image out of images)
In order to create a photographic mosaic, we need to map each pixel of the base image (the image we are trying to make out of many images) to an image from the dataset. To do this, we calculate the average RGB values of all images in the dataset and then map each pixel to the closes image RGB average
def get_pixel_median(img):
# cv2 reads BGR and NOT RGB
median = np.array([0, 0, 0])
height, width = img.shape[:2]
pixel_count = height * width
for row in img:
for pixel in row:
median += pixel
median = median // pixel_count
return median
def find_closest_color(color, colors):
b, g, r = color
color_diffs = []
for color in colors:
cb, cg, cr = color
color_diff = abs(b - cb) + abs(r - cr) + abs(g - cg)
color_diffs.append((color_diff, color))
return min(color_diffs)[1]Combining these two functions can help us map each pixel value to an image from the dataset
This program will be slower and slower as the images become larger and larger. So, the tqdm module has been used to show the progress of the program.
In addition, after calculating the average color of each image in the dataset, the data is saved in a JSON file so that the program won't have to calculate the same values over and over again each time it runs.
However, a drawback of this program is that the output image will be huge (>100 MB) if the input image was a bit large.
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
This example uses the Animals-10 dataset obtained from kaggle.com
