NanjingForestryUniversity/supermachine-tobacco
3
0
Fork 0
mirror of https://github.com/NanjingForestryUniversity/supermachine-tobacco.git synced 2025-11-08 14:23:55 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

计算误差测试版本

Browse Source
This commit is contained in:
FEIJINTI 2022-07-29 13:12:36 +08:00
parent d29d465c7c
commit 144b88543d
1 changed files with 49 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

54
main_test.py
View File

@ -3,6 +3,7 @@
# @Auther : zhouchao
# @File: main_test.py
# @Software:PyCharm
import itertools
import os
import time
@ -24,7 +25,7 @@ class TestMain:
background_model_path=Config.rgb_background_model_path)
def pony_run(self, test_path, test_spectra=False, test_rgb=False,
convert=False):
convert=False, get_delta=False):
"""
虚拟读图测试程序
@ -43,12 +44,12 @@ class TestMain:
with open(test_path, 'rb') as f:
data = f.read()
spec_img = transmit.BeforeAfterMethods.spec_data_post_process(data)
_ = self.test_spec(spec_img=spec_img)
_ = self.test_spec(spec_img=spec_img, img_name=test_path)
elif test_rgb:
with open(test_path, 'rb') as f:
data = f.read()
rgb_img = transmit.BeforeAfterMethods.rgb_data_post_process(data)
_ = self.test_rgb(rgb_img)
_ = self.test_rgb(rgb_img, img_name=test_path)
return
for rgb_file_name, spec_file_name in zip(rgb_file_names, spec_file_names):
if test_spectra:
@ -62,6 +63,16 @@ class TestMain:
rgb_img = transmit.BeforeAfterMethods.rgb_data_post_process(data)
rgb_mask = self.test_rgb(rgb_img, img_name=rgb_file_name)
if test_rgb and test_spectra:
if get_delta:
spec_cv = np.clip(spec_img[..., [21, 3, 0]], a_min=0, a_max=1) * 255
spec_cv = spec_cv.astype(np.uint8)
plt.imshow(spec_cv)
plt.show()
spec_cv = spec_cv.astype(np.uint8)
plt.imshow(spec_cv)
plt.show()
delta = self.calculate_delta(rgb_img, spec_cv)
print(delta)
self.merge(rgb_img=rgb_img, rgb_mask=rgb_mask,
spec_img=spec_img[..., [21, 3, 0]], spec_mask=spec_mask,
file_name=rgb_file_name)
@ -101,8 +112,41 @@ class TestMain:
plt.show()
return mask_result
def calculate_delta(self, rgb_img, spec_img):
rgb_grey, spec_grey = cv2.cvtColor(rgb_img, cv2.COLOR_RGB2GRAY), cv2.cvtColor(spec_img, cv2.COLOR_RGB2GRAY)
_, rgb_bin = cv2.threshold(rgb_grey, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
_, spec_bin = cv2.threshold(spec_grey, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
spec_bin = cv2.resize(spec_bin, dsize=(rgb_bin.shape[1], rgb_bin.shape[0]))
fig, axs = plt.subplots(2, 1)
axs[0].imshow(rgb_bin)
axs[1].imshow(spec_bin)
plt.show()
search_area = np.zeros_like(spec_bin)
for x in range(0, spec_bin.shape[0] // 10, 10):
for y in range(0, spec_bin.shape[1] // 10, 10):
delta_x, delta_y = x - spec_bin.shape[0] // 2, y - spec_bin.shape[1] // 2
rgb_cross_area = self.get_cross_area(rgb_bin, delta_x, delta_y)
spce_cross_area = self.get_cross_area(spec_bin, -delta_x, -delta_y)
response_altitude = np.sum(np.sum(rgb_cross_area & spce_cross_area))
search_area[x, y] = response_altitude
delta = np.argmax(search_area)
print(delta)
return delta
@staticmethod
def get_cross_area(img_bin, delta_x, delta_y):
if delta_x >= 0:
cross_area = img_bin[delta_x:, :]
else:
cross_area = img_bin[:delta_x, :]
if delta_y >= 0:
cross_area = cross_area[:, delta_y:]
else:
cross_area = cross_area[:, :delta_y]
return cross_area
if __name__ == '__main__':
testor = TestMain()
testor.pony_run(test_path=r'E:\zhouchao\728-tobacco\728-1-3',
test_rgb=True, test_spectra=True)
testor.pony_run(test_path=r'E:\zhouchao\728-tobacco\correct',
test_rgb=True, test_spectra=True, get_delta=True)