karl/ppv-lid-color-detector
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Extract most saturated color as probable lid color

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karl 2021-12-04 23:12:03 +01:00
parent 32b1625fde
commit 2c675f4176
1 changed files with 20 additions and 5 deletions
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25
detect.py
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@ -7,8 +7,11 @@ import matplotlib.pyplot as plt
import cv2
import numpy as np
from skimage import io
import colorsys
img = io.imread('https://i.stack.imgur.com/DNM65.png')[:, :, :-1]
img_path = 'IMG_20211204_220355.jpg'
img = io.imread(img_path)[:, :, :]
# Average color
average = img.mean(axis=0).mean(axis=0)
@ -36,11 +39,23 @@ dom_patch = np.zeros(shape=img.shape, dtype=np.uint8)
for i in range(len(rows) - 1):
dom_patch[rows[i]:rows[i + 1], :, :] += np.uint8(palette[indices[i]])
fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(12,6))
ax0.imshow(avg_patch)
ax0.set_title('Average color')
palette /= 255.0
def get_saturation(rgb_color):
return colorsys.rgb_to_hsv(*rgb_color)[1]
# Lid color is likely the color with the highest saturation
lid_color = max(palette, key=get_saturation)
fig, (ax0, ax1, ax2) = plt.subplots(1, 3, figsize=(12,4))
ax0.imshow(img)
ax0.set_title('Input')
ax0.axis('off')
ax1.imshow(dom_patch)
ax1.set_title('Dominant colors')
ax1.axis('off')
plt.show()
ax2.add_patch(matplotlib.patches.Rectangle((0, 0), 200, 200, color=lid_color))
ax2.set_title('Probable Lid Color')
ax2.axis('off')
plt.savefig(img_path + "_result.png")