python工具——pixellib详解编程语言

语义分割：将图像中每个像素赋予一个类别标签，用不同的颜色来表示 
实例分割：无需对每个像素进行标记，只需要找到感兴趣物体的边缘轮廓

pip3  install tensorflow 
pip3  install pillow 
pip3  install opencv-python 
pip3  install scikit-image 
pip3  install pixellib

import pixellib 
from pixellib.semantic import semantic_segmentation 
 
segment_image = semantic_segmentation() 
segment_image.load_pascalvoc_model("deeplabv3_xception_tf_dim_ordering_tf_kernels.h5") 
segment_image.segmentAsPascalvoc("test.jpg", output_image_name = "new.jpg")

import pixellib 
from pixellib.semantic import semantic_segmentation 
segment_image = semantic_segmentation() 
segment_image.load_pascalvoc_model("deeplabv3_xception_tf_dim_ordering_tf_kernels.h5") 
 
segment_image.segmentAsPascalvoc("test.jpg", output_image_name = "new1.jpg", overlay = True)

import pixellib 
from pixellib.semantic import semantic_segmentation 
import time 
segment_image = semantic_segmentation() 
segment_image.load_pascalvoc_model("deeplabv3_xception_tf_dim_ordering_tf_kernels.h5") 
start = time.time() 
segment_image.segmentAsPascalvoc("test.jpg", output_image_name = "new1.jpg", overlay = True) 
end = time.time() 
print(f"Inference Time: {end-start:.2f}seconds")

import pixellib 
from pixellib.instance import instance_segmentation 
import time 
segment_image = instance_segmentation() 
segment_image.load_model("mask_rcnn_coco.h5") 
start = time.time() 
segment_image.segmentImage("22.jpeg", output_image_name = "22new.jpg") 
end = time.time() 
print(f"Inference Time: {end-start:.2f}seconds")

import pixellib 
from pixellib.instance import instance_segmentation 
import time 
segment_image = instance_segmentation() 
segment_image.load_model("mask_rcnn_coco.h5") 
start = time.time() 
segment_image.segmentImage("22.jpeg", output_image_name = "22new1.jpg",show_bboxes = True) 
end = time.time() 
print(f"Inference Time: {end-start:.2f}seconds")