importcv2# 读取图像的字节数据defread_image_as_bytes(file_path):withopen(file_path,'rb')asf:returnf.read()# 示例文件路径file_path='example_image.jpg'image_bytes=read_image_as_bytes(file_path)# 打印读取的字节长度print(f'读取字节
# 导入必要的库defconvert_image_to_bytes(image_path):try:# 以二进制可读的方式打开图片文件withopen(image_path,'rb')asimage_file:# 利用read()方法读取文件数据image_bytes=image_file.read()returnimage_bytesexceptIOError:print("Error: Unable to open the image file.")# 使用示例image_path='exampl...
train.BytesList(value=[img_raw])) })) #example对象对label和image数据进行封装 writer.write(example.SerializeToString()) #序列化为字符串 writer.close() 在制作完成我们的数据集后需要读取: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 import tensorflow as tf def read_and_decode(filename): #...
"rb") as f:#读取图片的二进制数据bin_contents = f.read()# 使用opencv读取图片img = cv2.imread(img_path)# 将numpy的数组转换为bytesarray_bytes = img.tobytes()# 或者使用img.tostring()# 对数组的图片格式进行编码success, encoded_image = cv2.imencode(".jpg", img)# 将数组转为bytesimg_bytes...
numpy as np # 假设 img_bytes 是你的图片的二进制数据 def read_image_from_bytes(img_bytes):...
在OpenCV中,虽然没有直接的 from_buffer 或from_bytes 方法,但你可以使用 numpy 的frombuffer 方法将二进制数据转换为 numpy 数组,然后通过 OpenCV 的 imdecode 来读取图片。 import cv2 import numpy as np # 假设 img_bytes 是你的图片的二进制数据 def read_image_from_bytes(img_bytes): # 1. 使用 numpy...
import numpy as np import io from PIL import Image def string_to_image(string, width, height): image = Image.frombytes('RGB', (width, height), string) return image # 连接到摄像头 cam_ip = 'http://192.168.1.64' cam_username = 'admin' ...
返回类型是numpy.array,可以设置编码类型:ASCII latin1 bytes等, 回到顶部 3、图片文件:jpg、jpeg、png等 读取图片文件常用3个函数 (1)skimage库的 io.imread()函数 1 import skimage.io as io 2 data = io.imread(‘dirpath/figure1.jpg’) scikit-image是基于scipy的一款图像处理包,它将图片作为numpy数组...
import base64 import cv2 import numpy as np from ai_service_python_sdk.client.api.ai_service_aigc_images_api import \ AIGCImagesApi # noqa: E501 from ai_service_python_sdk.client.api_client import ApiClient def decode_image_from_base64jpeg(base64_image): image_bytes = base64.b64decode...
Website: https://imageio.readthedocs.io/Imageio is a mature Python library that makes it easy to read and write image and video data. This includes animated images, video, volumetric data, and scientific formats. It is cross-platform, runs on Python 3.9+, and is easy to install....