在板端推理时,经常会将png图片转成.bgr为后缀的二进制图片,偶尔也需要将.bgr转为png图片查看,这两者之间的互相转换,代码实现如下:
import cv2
import numpy as np
def png2bgr():
img_path = r'C:\Code\test_qua_detect_img/res.png'.replace('\\', '/') # 原图地址
save_path = 'C:/imgs'+'/'+'res.bgr' # 转成二进制的存储地址
img = cv2.imread(img_path) # cv2 读取的图片本来就是bgr格式的,因此通过opencv转换非常方便
img = cv2.resize(img, (320, 320))
shape = img.shape
print(shape) # shape 是 [w, h, 3]
# 使用一个元组收取BGR3通道的
(B, G, R) = cv2.split(img)
with open(save_path, 'wb') as fp:
for i in range(320):
for j in range(320):
fp.write(B[i, j])
# print(B[i, j])
for i in range(320):
for j in range(320):
fp.write(G[i, j])
# print(G[i, j])
for i in range(320):
for j in range(320):
fp.write(R[i, j])
# print(G[i, j])
print("write success!")
def bgr2png():
bgr_path = r'C:\imgs/res.bgr'.replace('\\', '/')
save_dir = r'C:/imgs/'
f = open(bgr_path, "rb")
d = f.read()
tmp_a = []
for i in d:
tmp_a.append(i)
tmp_a = np.array(tmp_a, dtype=np.uint8)
print(tmp_a.shape)
B = tmp_a[:102400].reshape(320, 320,1)
G = tmp_a[102400:204800].reshape(320, 320,1)
R = tmp_a[204800:].reshape(320, 320,1)
image = np.concatenate((B,G,R),axis=2)
print(image.shape)
# data = np.fromfile(bgr_path, np.uint8).reshape(320, 320, 3)
cv2.imshow("res.png", image)
cv2.imwrite(save_dir+'/'+'res.png', image)
cv2.waitKey(0)
print("read success!")
if __name__ == '__main__':
# png转二进制bgr图片
png2bgr()
# 二进制图片转png
bgr2png()