我已经创建了一个带有Raspberry Pi的MLX90640热摄像机的代码。
守则如下:
import time,board,busio
import numpy as np
import adafruit_mlx90640
import matplotlib.pyplot as plt
print("Initializing MLX90640")
i2c = busio.I2C(board.SCL, board.SDA, frequency=800000) # setup I2C
mlx = adafruit_mlx90640.MLX90640(i2c) # begin MLX90640 with I2C comm
mlx.refresh_rate = adafruit_mlx90640.RefreshRate.REFRESH_2_HZ # set refresh rate
mlx_shape = (24,32)
print("Initialized")
# setup the figure for plotting
plt.ion() # enables interactive plotting
fig,ax = plt.subplots(figsize=(12,7))
therm1 = ax.imshow(np.zeros(mlx_shape),vmin=0,vmax=60) #start plot with zeros
cbar = fig.colorbar(therm1) # setup colorbar for temps
cbar.set_label('Temperature [$^{\circ}$C]',fontsize=14) # colorbar label
frame = np.zeros((24*32,)) # setup array for storing all 768 temperatures
t_array = []
print("Starting loop")
while True:
t1 = time.monotonic()
try:
mlx.getFrame(frame) # read MLX temperatures into frame var
data_array = (np.reshape(frame,mlx_shape)) # reshape to 24x32
therm1.set_data(np.fliplr(data_array)) # flip left to right
therm1.set_clim(vmin=np.min(data_array),vmax=np.max(data_array)) # set bounds
cbar.update_normal(therm1) # update colorbar range
plt.title(f"Max Temp: {np.max(data_array):.1f}C")
plt.pause(0.001) # required
#fig.savefig('mlx90640_test_fliplr.png',dpi=300,facecolor='#FCFCFC', bbox_inches='tight') # comment out to speed up
t_array.append(time.monotonic()-t1)
print('Sample Rate: {0:2.1f}fps'.format(len(t_array)/np.sum(t_array)))
except ValueError:
continue # if error, just read again它展示了这个输出:
在右上角,您可以看到所检测到的最高热量的x和y坐标。
我遇到的问题是根据图像的中间而不是左下角来定位坐标。
我试图将输出中间的(0,0)的x和y点定向,并将x和y坐标分别从图中打印出来。
我确信有一行代码我可以输入或更改,但我遇到了最严重的麻烦。
发布于 2022-10-23 02:08:26
使用extent
extent = (-16, 16, 12.5, -12.5)您可以在imshow中使用它
therm1 = ax.imshow(np.zeros(mlx_shape),vmin=0,vmax=60, extent=extent) #start plot with zeros或者直接在therm1上
therm1.set(extent=extent) # matplotlib version 3.5+
therm1.set_extent(extent) # version 3.4发布于 2022-10-23 10:58:04

这是你想要的吗?
In [76]: fig, ax = plt.subplots(layout='constrained')
...: ax.imshow(img, extent=(-12.5,11.5,-17.5,18.5))
...: ax.spines[["left", "bottom"]].set_position(("data", 0))
...: ax.spines[["top", "right"]].set_visible(False)
...: ax.spines[["left", "bottom"]].set_color('w')
...: ax.tick_params(axis='both', which='both', color='w')
...: for label in ax.xaxis.get_majorticklabels():
...: label.set_color('w')
...: label.set_bbox(dict(facecolor='k', alpha=.3))
...: for label in ax.yaxis.get_majorticklabels():
...: label.set_color('w')
...: label.set_bbox(dict(facecolor='k', alpha=.3))哦,是的,滴答标签周围较暗的边缘很烦人,但目前我不知道如何去除它们:如果OP告诉我这几乎是他们想要的,我可以调查.
https://stackoverflow.com/questions/74167774
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