117 lines
3.3 KiB
Python
117 lines
3.3 KiB
Python
import cv2
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import numpy as np
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import os
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import numpy as np
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import cv2
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import matplotlib.pyplot as plt
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# # 创建一个空白图像（假设大小为100x100）
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# height, width = 100, 100
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# segmentation_result = np.zeros((height, width), dtype=np.uint8)
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# # 创建一些分割区域
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# segmentation_result[10:30, 10:30] = 50 # 区域1
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# segmentation_result[40:60, 40:60] = 100 # 区域2
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# segmentation_result[70:90, 70:90] = 150 # 区域3
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# segmentation_result[20:50, 70:90] = 200 # 区域4
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# # 保存图像
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# cv2.imwrite('segmentation_result.png', segmentation_result)
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# segmentation_result = cv2.imread('segmentation_result.png', cv2.IMREAD_GRAYSCALE)
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# height, width = segmentation_result.shape
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# fig = plt.figure()
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# ax = fig.add_subplot(111, projection='3d')
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# unique_labels = np.unique(segmentation_result)
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# heights = np.linspace(1, 10, len(unique_labels)) # 高度范围从1到10，可以根据需要调整
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# for i, label in enumerate(unique_labels):
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# mask = (segmentation_result == label)
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# x, y = np.meshgrid(np.arange(width), np.arange(height))
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# x = x[mask]
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# y = y[mask]
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# z = np.zeros_like(x)
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# dz = np.full_like(x, heights[i])
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# ax.bar3d(x, y, z, 1, 1, dz, shade=True)
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# ax.set_xlabel('X axis')
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# ax.set_ylabel('Y axis')
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# ax.set_zlabel('Height')
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# plt.show()
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def categorize_pixels(image_path, output_dir):
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# 读取图像
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image = cv2.imread(image_path)
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if image is None:
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print("Error: Unable to read image.")
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return
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# 创建输出目录
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if not os.path.exists(output_dir):
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os.makedirs(output_dir)
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# 获取图像的高度和宽度
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height, width, _ = image.shape
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# 创建类别掩码
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categories = np.zeros((height, width), dtype=np.uint8)
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# 遍历每个像素并分类
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for y in range(height):
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for x in range(width):
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r, g, b = image[y, x]
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rgb_sum = int(r) + int(g) + int(b)
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# if b != 0:
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# continue
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if rgb_sum <= 0: # label 1
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categories[y, x] = 50
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elif rgb_sum <= 120: # label 2
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categories[y, x] = 100
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elif rgb_sum < 200: # label 3
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categories[y, x] = 150
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else: # label 4
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categories[y, x] = 200
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cv2.imwrite("deeptmp.png",categories)
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segmentation_result = cv2.imread("./deeptmp.png", cv2.IMREAD_GRAYSCALE)
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height, width = segmentation_result.shape
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print("正在生成三维图...")
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fig = plt.figure()
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ax = fig.add_subplot(111, projection='3d')
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unique_labels = np.unique(segmentation_result)
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heights = [10, 5, 3, 1]
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#heights = np.linspace(10, 1, len(unique_labels)) # 高度范围从1到10，可以根据需要调整
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for i, label in enumerate(unique_labels):
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mask = (segmentation_result == label)
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x, y = np.meshgrid(np.arange(width), np.arange(height))
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x = x[mask]
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y = y[mask]
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z = np.zeros_like(x)
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dz = np.full_like(x, heights[i])
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ax.bar3d(x, y, z, 1, 1, dz, shade=True)
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ax.set_xlabel('X axis')
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ax.set_ylabel('Y axis')
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ax.set_zlabel('Height')
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plt.show()
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if __name__ == "__main__":
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image_path = "./fill.png" # 替换为你的图像路径
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output_dir = "./"
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categorize_pixels(image_path, output_dir)
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print(f"Pixel categorization complete. Results saved in {output_dir}")
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