<jupyter_start><jupyter_text><jupyter_code>import cv2
from google.colab.patches import cv2_imshow
src = cv2.imread('./bicycle.png', cv2.IMREAD_UNCHANGED)
src_rgb = cv2.cvtColor(src, cv2.COLOR_BGR2RGB)
cv2_imshow(src)
import numpy as np
low_yellow = np.array([221, 195, 5])
high_yellow = np.array([255, 208, 58])
mask = cv2.inRange(src_rgb, low_yellow, high_yellow)
result_src = cv2.bitwise_and(src, src, mask = mask)
cv2_imshow(result_src)
low_yellow = np.array([0, 192, 0])
high_yellow = np.array([255, 255, 255])
src_hsv = cv2.cvtColor(src, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(src_hsv, low_yellow, high_yellow)
result_src = cv2.bitwise_and(src, src, mask = mask)
cv2_imshow(result_src)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1376912378303199, 'fraction_numerical': 0.06397774687065369, 'mean_word_length': 7.181818181818182, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '433552', 'license': 'MIT', 'n_tokens_mistral': 343, 'n_tokens_neox': 308, 'n_words': 56, 'path': 'bicycle_rgb_hsv.ipynb', 'repo_name': 'JSJeong-me/OpenCV_Practitioner_Guide_1', 'size': '719'}