# os.system(cmd_str) # else: # cmd_str = 'python run_color_black.py -c '+str(images_num)+' -w 5 -f 64 -b 3 -t 8 -bl 1 -rbl -cs 5 -k 5 -rk -d 1 -ft fonts/cn/' + ttfname + '.ttf -id images -i out/number.txt --output_dir out/out_black_' + ttfname + '...
Synthetic Text Image Generator for OCR Model |Paper|Documentation|Datasets Contents Documentation Installation Usage Advanced Usage Datasets Citation License Documentation The documentation is available athttps://clovaai.github.io/synthtiger/. You can check API reference in this documentation. ...
1fromrandomimportrandint234defmakeDict(text):5#替换换行符和引号6text = text.replace('\n','')7text = text.replace('\“','')8text = text.replace('\”','')910punc = [',','。','?',';',':','!']11forsymbolinpunc:12text = text.replace(symbol,''+symbol+'')1314words = [wo...
本项目在萤火二号集群上用 PyTorch 实现了论文 《CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP》。 CLIP-GEN 是一个 Language-Free 的文本生成图像的方法,它不依赖图文训练样本,通过预训练 CLIP 模型的强大表征能力,只需要图片数据就可以训练出一个文本生成图像的模型。该方法的基本...
Basic usage python train.py --data_set="flowers" Options z_dim: Noise Dimension. Default is 100. t_dim: Text feature dimension. Default is 256. batch_size: Batch Size. Default is 64. image_size: Image dimension. Default is 64. gf_dim: Number of conv in the first layer generator. ...
squeeze(1), hidden import paddle import paddle.nn as nn # define the generator class Generator(nn.Layer): def __init__(self, noise_dim, projected_embed_dim, ngf): super(Generator, self).__init__() self.num_channels = 3 self.image_size = 64 self.noise_dim = noise_dim self.embed...
python main.py --validation --split=2 --pretrain_model=model/netG.pdparams 使用预训练模型预测 将需要测试的文件放在参数pretrain_model确定的目录下,运行下面指令,输出图片保存在image\目录中 python main.py --validation --split=2 --pretrain_model=model/netG.pdparams LICENSE 本项目所遵守的开源协...
Caption Generator》https://arxiv.org/pdf/1411.4555.pdf 该论文中的Encoder结构,修改为CNN 以用于ImageCaption...Attention》https://arxiv.org/pdf/1502.03044v1.pdf 该论文又进一步引入了注意力机制。 Abstract:Inspired by recent work in Image Caption论文合辑2 ...
Define if the generator will return masks for the text 定义生成器是否将返回文本的掩码 -d [DISTORSION], --distorsion [DISTORSION] Define a distorsion applied to the resulting image. 0:None (Default), 1: Sine wave, 2: Cosine wave, 3:Random ...
Let’s create a business name generator using prompt templates that will return five to seven relevant business names: from langchain_openai.chat_models import ChatOpenAI from langchain_core.prompts import (SystemMessagePromptTemplate, ChatPromptTemplate) template = """ You are a creative consultant...