Loovelj
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| # 该函数用于统计 TFRecord 文件中的样本数量(总数) | |
| def total_sample(file_name): | |
| sample_nums = 0 | |
| for record in tf.python_io.tf_record_iterator(file_name): | |
| # for record in tf.data.TFRecordDataset(path) | |
| sample_nums += 1 | |
| return sample_nums |
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| def resize_img_720p(img): | |
| h,w = img.shape[:2] | |
| new_h = max(h,w) | |
| fx = 1280/new_h | |
| resize_img = cv2.resize(img,(0, 0), fx = fx, fy = fx, interpolation = cv2.INTER_LINEAR) | |
| img_encode = cv2.imencode('.jpg', resize_img) | |
| str_encode = img_encode[1].tostring() | |
| return resize_img, str_encode |
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| import sys | |
| import ruamel.yaml | |
| yaml = ruamel.yaml.YAML() | |
| # yaml.preserve_quotes = True | |
| def up_yml(model_name): | |
| with open('version.yaml') as fp: | |
| data = yaml.load(fp) | |
| data[1]["model_path"] = "test_model/" + model_name |
Loovelj
/ plt_to_latex_img.py
Last active
January 20, 2020 10:55
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| import numpy as np | |
| import matplotlib.pyplot as plt | |
| fig = plt.figure() | |
| ax = fig.add_subplot(111) | |
| ax.set_xlim([1, 10]) | |
| ax.set_ylim([1, 10]) |
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| class AlignCollate(object): | |
| def __init__(self, img_height=32, img_width=100): | |
| self.img_height = img_height | |
| self.img_width = img_width | |
| self.transform = ResizeNormalize(img_width=self.img_width, img_height=self.img_height) | |
| def __call__(self, batch): | |
| images, labels = zip(*batch) |
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| import glob | |
| import os | |
| file_list = glob.glob('/data/data/huansuan/image/*') | |
| for file in file_list: | |
| new_name = file.replace('-','_') | |
| os.rename(file,new_name) | |
| print(file,new_name) |
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| def resize_img_720p(img): | |
| h,w = img.shape[:2] | |
| new_h = max(h,w) | |
| fx = 1280/new_h | |
| resize_img = cv2.resize(img,(0, 0), fx = fx, fy = fx, interpolation = cv2.INTER_LINEAR) | |
| return resize_img |
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| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| import os | |
| import time | |
| import json | |
| import time as time | |
| import tensorflow as tf |
Loovelj
/ ctc_decoder.py
Created
August 13, 2019 06:36
— forked from awni/ctc_decoder.py
Example CTC Decoder in Python
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| """ | |
| Author: Awni Hannun | |
| This is an example CTC decoder written in Python. The code is | |
| intended to be a simple example and is not designed to be | |
| especially efficient. | |
| The algorithm is a prefix beam search for a model trained | |
| with the CTC loss function. |
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| import requests | |
| import os | |
| with open(r'D:\liujun\20-31.txt','r',encoding='utf-8') as f: | |
| file_list=f.readlines() | |
| for file in file_list: | |
| file=file.replace('\n','') | |
| base_name=os.path.basename(file) | |
| try: | |
| url =file |
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