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cvlab-stonybrook / LearningToCountEverything

MIT License
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Hello, could you tell me how the density map is generated #40

Open Transformer-man opened 1 year ago

Transformer-man commented 1 year ago

how the density map is generated？

QQ截图20230314154255

Tom-Medicine commented 1 year ago

好兄弟你知道了吗，我大概了解了不知道是不是对的，就是他通过高斯核生成的

Transformer-man commented 1 year ago

他有代码可以直接生成的

Tom-Medicine commented 1 year ago

好兄弟，细说，我做的这个毕设，之前我直接用的他的数据集，结果现在要改数据集，改成专门计人的，咋生成的啊？

liwead commented 1 year ago

他有代码可以直接生成的

请问你，生成密度图的代码在哪里呀，如果能告诉我的话不胜感激

Tom-Medicine commented 7 months ago

谢谢好兄弟，研究生没考上，最近在找工作，近期没时间学深度学习了

------------------ 原始邮件 ------------------ 发件人: "cvlab-stonybrook/LearningToCountEverything" @.>; 发送时间: 2023年12月11日(星期一) 下午5:28 @.>; @.**@.>; 主题: Re: [cvlab-stonybrook/LearningToCountEverything] Hello, could you tell me how the density map is generated (Issue #40)

姿态估计中有类似的方法 def putGaussianMaps(center, accumulate_confid_map, sigma, grid_y, grid_x, stride): start = stride / 2.0 - 0.5 y_range = [i for i in range(int(grid_y))] x_range = [i for i in range(int(grid_x))] xx, yy = np.meshgrid(x_range, y_range) xx = xx stride + start yy = yy stride + start d2 = (xx - center[0]) 2 + (yy - center[1]) 2 exponent = d2 / 2.0 / sigma / sigma mask = exponent <= 4.6052 cofid_map = np.exp(-exponent) cofid_map = np.multiply(mask, cofid_map) accumulate_confid_map += cofid_map accumulate_confid_map[accumulate_confid_map > 1.0] = 1.0 return accumulate_confid_map
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