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Good day to all, I am trying to create a heatmap, given a set of x, y coordinate pairs extracted from a CSV file. I am using numpy.histogram2d to plot it, the heatmap gives me correct, but I need to overlay it on another image. I share my code

Here is the CSV

csv = pd.read_csv("../test2.csv")
#Gets the centroid of the coords
csv["x"] = (combined_csv["x_min"]+(combined_csv["x_max"]-combined_csv["x_min"])/2).astype(int) 
csv["y"] = (combined_csv["y_min"]+(combined_csv["y_max"]-combined_csv["y_min"])/2).astype(int)
am = csv[(csv["tracking_id"] != 7) &(csv["tracking_id"] != 28)] #Some filters

#Taken from another question
def myplot(x, y, s, bins=1000):
    heatmap, xedges, yedges = np.histogram2d(x, y, bins=bins, range=[[0, 960], [0, 480]])
    heatmap = gaussian_filter(heatmap, sigma=s)
    extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]
    return heatmap.T, extent
img, extent = myplot(am["x"], am["y_max"], 16,200)
plt.imshow(img, extent=extent, origin='upper', cmap=cm.jet)

The previous code gives me this image

Heatmap with correct extents

I put the range between 0 and 480 for x and 0 and 960 for y, because the target image has that size, but doing this, histogram2d returns me the histogram matrix h, which is 200x200, then I use matplotlib to plot it and This graphs me correctly in the range 0-480 for x and 0-960 for y, what I need is to save said image, preserving as much information as possible in the 480x960 pixel size, and then add it with the target image using this tutorial how to superimpose heatmap on a base image?

final_img = cv2.addWeighted (heatmap_img, 0.5, image, 0.5, 0)

For creating something like this Example of what i wanted But the image and the histogram doesnt match in the sizes that i wanted. This is the target image Target image

Daniel Hoyos González
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1 Answers1

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Ok, so i fix the error by the next code, printing the two images at the same plot

base_image = image
sigma = 8
fig, ax = plt.subplots(1, 1, figsize = (20, 16))
heatmap, xedges, yedges = np.histogram2d(am["x"], am["y"], bins=200, range=[[0,960],[0,480]])
heatmap = gaussian_filter(heatmap, sigma=sigma)
extent = [xedges[0], xedges[-1], yedges[-1], yedges[0]]
img = heatmap.T
ax.imshow(img, extent=extent, cmap=cm.jet)
ax.imshow(base_image, alpha = 0.5)
ax.set_xlim(0, 960)
ax.set_ylim(480,0)
ax.axes.get_yaxis().set_visible(False)
ax.axes.get_xaxis().set_visible(False)
plt.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=0, hspace=0)
plt.savefig("heatmap_final.png", bbox_inches='tight')
plt.show()
plt.close(fig)
Daniel Hoyos González
  • 11
  • 2