def webp_enc(self, x, quality):
shape = (8, 16)
data = copy.copy(x)
fmap_images_with_info = feature_maps_to_image(
data, shape, is_display=0, is_save=0)
encode_param = [int(cv2.IMWRITE_WEBP_QUALITY), quality]
result, encimg = cv2.imencode(
'.webp', fmap_images_with_info[0][0], encode_param)
self.compressed_mem = len(encimg)
print(len(encimg), "length of encoded image")
res = (encimg, fmap_images_with_info[0][1])
return res
def jpeg_enc(self, feature_maps, quality):
"""
feature_maps: output tensor of feature maps in shape (1, 78, 78, 128)
quality: quality of JPEG lossy compression from 0 - 100
return: sliced image of feature maps, pixel from 0 - 255
"""
shape = (8, 16)
fmap_images_with_info = feature_maps_to_image(
feature_maps, shape, is_display=0, is_save=0)
encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), quality]
result, encimg = cv2.imencode(
'.jpg', fmap_images_with_info[0][0], encode_param)
self.compressed_mem = len(encimg)
# print(len(encimg), "length of encoded image")
res = (encimg, fmap_images_with_info[0][1])
return res