mirror of
https://github.com/NanjingForestryUniversity/supermachine--tomato-passion_fruit.git
synced 2025-11-08 22:34:00 +00:00
89 lines
3.5 KiB
Python
89 lines
3.5 KiB
Python
import cv2
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import numpy as np
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import matplotlib.pyplot as plt
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import os
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def create_mask(hsv_image, hue_value, hue_delta, value_target, value_delta):
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# 创建H通道阈值掩码
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lower_hue = np.array([hue_value - hue_delta, 0, 0])
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upper_hue = np.array([hue_value + hue_delta, 255, 255])
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hue_mask = cv2.inRange(hsv_image, lower_hue, upper_hue)
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# 创建V通道排除中心值的掩码
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lower_value_1 = np.array([0, 0, 0])
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upper_value_1 = np.array([180, 255, value_target - value_delta])
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lower_value_2 = np.array([0, 0, value_target + value_delta])
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upper_value_2 = np.array([180, 255, 255])
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value_mask_1 = cv2.inRange(hsv_image, lower_value_1, upper_value_1)
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value_mask_1 = cv2.bitwise_not(value_mask_1)
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cv2.imshow('value_mask_1', value_mask_1)
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value_mask_2 = cv2.inRange(hsv_image, lower_value_2, upper_value_2)
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cv2.imshow('value_mask_2', value_mask_2)
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value_mask = cv2.bitwise_and(value_mask_1, value_mask_2)
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cv2.imshow('value_mask', value_mask)
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# 等待用户按下任意键
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cv2.waitKey(0)
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# 关闭所有窗口
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cv2.destroyAllWindows()
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# 合并H通道和V通道掩码
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return cv2.bitwise_and(hue_mask, value_mask)
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def apply_morphology(mask):
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kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
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return cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
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def find_largest_component(mask):
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num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(mask, 4, cv2.CV_32S)
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if num_labels < 2:
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return None # No significant components found
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max_label = 1 + np.argmax(stats[1:, cv2.CC_STAT_AREA]) # Skip background
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return (labels == max_label).astype(np.uint8) * 255
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def process_image(image_path, hue_value=37, hue_delta=10, value_target=25, value_delta=10):
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image = cv2.imread(image_path)
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if image is None:
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print(f"Error: Image at {image_path} could not be read.")
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return None
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hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
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combined_mask = create_mask(hsv_image, hue_value, hue_delta, value_target, value_delta)
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combined_mask = apply_morphology(combined_mask)
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max_mask = find_largest_component(combined_mask)
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cv2.imshow('max_mask', max_mask)
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# 等待用户按下任意键
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cv2.waitKey(0)
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# 关闭所有窗口
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cv2.destroyAllWindows()
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if max_mask is None:
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print(f"No significant components found in {image_path}.")
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return None
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result_image = cv2.bitwise_and(image, image, mask=max_mask)
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result_image[max_mask == 0] = [255, 255, 255] # Set background to white
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return result_image
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def save_image(image, output_path):
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cv2.imwrite(output_path, image)
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def process_images_in_folder(input_folder, output_folder):
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if not os.path.exists(output_folder):
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os.makedirs(output_folder)
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for filename in os.listdir(input_folder):
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if filename.lower().endswith(".bmp"):
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image_path = os.path.join(input_folder, filename)
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result_image = process_image(image_path)
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if result_image is not None:
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output_path = os.path.join(output_folder, filename)
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save_image(result_image, output_path)
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print(f"Processed and saved {filename} to {output_folder}.")
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# 主函数调用
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input_folder = r'D:\project\supermachine--tomato-passion_fruit\20240529RGBtest3\data\passion_fruit_img' # 替换为你的输入文件夹路径
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output_folder = r'D:\project\supermachine--tomato-passion_fruit\20240529RGBtest3\data\01' # 替换为你的输出文件夹路径
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process_images_in_folder(input_folder, output_folder) |