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image_demo.py
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image_demo.py
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#! /usr/bin/env python
# coding=utf-8
#================================================================
# Copyright (C) 2019 * Ltd. All rights reserved.
#
# Editor : VIM
# File name : image_demo.py
# Author : YunYang1994
# Created date: 2019-01-20 16:06:06
# Description :
#
#================================================================
import cv2
import numpy as np
import core.utils as utils
import tensorflow as tf
from PIL import Image
return_elements = ["input/input_data:0", "pred_sbbox/concat_2:0", "pred_mbbox/concat_2:0", "pred_lbbox/concat_2:0"]
pb_file = "./yolov3_96_coco.pb"
image_path = "./0C006B5C.jpg"
num_classes = 1
input_size = 544
graph = tf.Graph()
original_image = cv2.imread(image_path)
original_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2RGB)
original_image_size = original_image.shape[:2]
image_data = utils.image_preporcess(np.copy(original_image), [input_size, input_size])
image_data = image_data[np.newaxis, ...]
return_tensors = utils.read_pb_return_tensors(graph, pb_file, return_elements)
with tf.Session(graph=graph) as sess:
pred_sbbox, pred_mbbox, pred_lbbox = sess.run(
[return_tensors[1], return_tensors[2], return_tensors[3]],
feed_dict={ return_tensors[0]: image_data})
pred_bbox = np.concatenate([np.reshape(pred_sbbox, (-1, 5 + num_classes)),
np.reshape(pred_mbbox, (-1, 5 + num_classes)),
np.reshape(pred_lbbox, (-1, 5 + num_classes))], axis=0)
print(pred_bbox)
bboxes = utils.nms(pred_bbox, 0.45, method='soft-nms')
bboxes = utils.postprocess_boxes(pred_bbox, original_image_size, input_size, 0.6)
#bboxes = utils.nms(bboxes, 0.45, method='nms')
image = utils.draw_bbox(original_image, bboxes)
#image = Image.fromarray(image).resize((2666,2000),Image.ANTIALIAS)
#image = cv2.resize(image,(2666,2000))
image = Image.fromarray(image)
image.show()
image.save('a.jpg')