tensorflow處理影象函式
阿新 • • 發佈:2018-12-13
import matplotlib.pyplot as plt; import tensorflow as tf; img_raw = tf.gfile.FastGFile('path/output.jpg', 'rb').read() img = tf.image.decode_jpeg(img_raw) img = tf.image.convert_image_dtype(img, dtype=tf.float32) with tf.Session() as sess: #按照比例 resized = tf.image.central_crop(img,0.5) #影象翻轉 resized=tf.image.flip_left_right(img); resized=tf.image.flip_up_down(img); #影象色彩調整 resized=tf.image.adjust_brightness(img,-0.5); resized=tf.image.adjust_brightness(img,0.5); #對比度調整 resized=tf.image.adjust_contrast(img,-5); resized=tf.image.adjust_contrast(img,5); #調整影象色相 resized=tf.image.adjust_hue(img,0.67); #調整飽和度 resized=tf.image.adjust_saturation(img,-5); #將影象標準化,就是將數字均值變為0,方差變成1 resized=tf.image.per_image_standardization(img); #處理標註框 batched=tf.expand_dims(img,0); boxes=tf.constant([[[0.05,0.04,0.05,0.04],[0.06,0.04,0.04,0.04]]]); resized=tf.image.draw_bounding_boxes(batched,boxes); print(resized); # plt.imshow(resized.eval()) # plt.show()