阈值后温度为黑色

本文介绍了阈值后温度为黑色的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我想根据密度显示温度.

I want to show the temperature based on the density.

以下是Im使用的功能

def add_heat(heatmap, bbox_list): for i in range(len(bbox_list)): rect = trackers[i].get_position() heatmap[int(rect.left()):int(rect.top()), int(rect.right()):int(rect.bottom())] += 1 return heatmap def apply_threshold(heatmap, threshold): # Zero out pixels below the threshold heatmap[heatmap <= threshold] = 0 # Return thresholded map cv2.imwrite("heatmap.png",heatmap) return heatmap

add_heat函数将遍历跟踪器，并仅针对阈值调整那些特定区域上的热图.

apply_threshold会将低于阈值的所有像素转换为零.

add_heat function will loop through the trackers and will tweak the heatmap only on those specific areas for the thresholding

apply_threshold will convert all pixels to zero if it is below certain threshold.

我这样称呼它，

heat = np.zeros_like(frame[:, :, 0]).astype(np.float) heat = add_heat(heat,trackers) heat = apply_threshold(heat, 80) heatmap = np.clip(heat, 0, 255)

trackers包含所有跟踪的坐标.但是，当我尝试显示最终结果时，它仍然是黑色的.我可以知道我在想什么吗?

trackers contains all the tracked coordinates. however when i try to show the final result, it is still black. May i know what am i missing?

推荐答案

似乎您的问题出在这里:

Seems like your problem lies in here:

heatmap[int(rect.left()):int(rect.top()), int(rect.right()):int(rect.bottom())] += 1 return heatmap

假设您想将热图与skimage一起使用，您可能应该这样做:

Assuming you want to use the heatmap with something like skimage, you should probably do it like this:

heatmap[top_row:bottom_row, leftmost_column:rightmost_column]

在您的代码中它将如下所示:

which in your code will look like this:

heatmap[int(rect.bottom()):int(rect.top()), int(rect.left()):int(rect.right())] += 1 return heatmap

您可能想了解有关numpy数组的更多信息. 当我看到此问题在哪里时，我能够说出正在发生什么情况起源.

You may want to read a little more about numpy arrays. I was able to tell what is happening as I saw where this question originated.