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| from upcunet_v3 import RealWaifuUpScaler | |
| import gradio as gr | |
| import time | |
| import logging | |
| import os | |
| from PIL import ImageOps | |
| import numpy as np | |
| import math | |
| def greet(input_img, input_model_name, input_tile_mode): | |
| # if input_img.size[0] * input_img.size[1] > 256 * 256: | |
| # y = int(math.sqrt(256*256/input_img.size[0]*input_img.size[1])) | |
| # x = int(input_img.size[0]/input_img.size[1]*y) | |
| # input_img = ImageOps.fit(input_img, (x, y)) | |
| input_img = np.array(input_img) | |
| if input_model_name not in model_cache: | |
| t1 = time.time() | |
| upscaler = RealWaifuUpScaler(input_model_name[2], ModelPath + input_model_name, half=False, device="cpu") | |
| t2 = time.time() | |
| logger.info(f'load model time, {t2 - t1}') | |
| model_cache[input_model_name] = upscaler | |
| else: | |
| upscaler = model_cache[input_model_name] | |
| logger.info(f'load model from cache') | |
| start = time.time() | |
| result = upscaler(input_img, tile_mode=input_tile_mode) | |
| end = time.time() | |
| logger.info(f'input_model_name, {input_model_name}') | |
| logger.info(f'input_tile_mode, {input_tile_mode}') | |
| logger.info(f'input shape, {input_img.shape}') | |
| logger.info(f'output shape, {result.shape}') | |
| logger.info(f'speed time, {end - start}') | |
| return result | |
| if __name__ == '__main__': | |
| logging.basicConfig(level=logging.INFO, format="[%(asctime)s] [%(process)d] [%(levelname)s] %(message)s") | |
| logger = logging.getLogger() | |
| ModelPath = "weights_v3/" | |
| model_cache = {} | |
| input_model_name = gr.inputs.Dropdown(os.listdir(ModelPath), default="up4x-latest-conservative.pth", label='选择放大倍数及降噪模式') | |
| input_tile_mode = gr.inputs.Dropdown([0, 1, 2, 3, 4], default=2, label='tile图像输出平铺模式') | |
| input_img = gr.inputs.Image(label='长安棉花糖♣ ♣点击下方上传图像（不超2MB）', type='pil') | |
| inputs = [input_img, input_model_name, input_tile_mode] | |
| outputs = "image" | |
| iface = gr.Interface(fn=greet, | |
| inputs=inputs, | |
| outputs=outputs, | |
| allow_screenshot=False, | |
| allow_flagging='never', | |
| examples示例=[['efwe0.jpg',]], | |
| article='♣棉花糖AI团队学员使用版♣<br>' | |
| '感谢b站开源的项目-Real CUGAN，由于使用的是免费的cpu，使用空间有限，上传的图片过大将会导致内存不足，请尽量不要上传超过 2Mb 的图片！<br>' | |
| '如在使用过程中出现放大不了或内存已满16G的情况，请及时告知群管理：星河或者17老师，以便重新启动程序<br>' | |
| '放大模式使用说明：<br>' | |
| '1.降噪版(denoise)：如果原片噪声多，压得烂，推荐使用；目前2倍模型支持了3个降噪等级<br>' | |
| '2.无降噪版(no-denoise)：如果原片噪声不多，压得还行，但是想提高分辨率/清晰度/做通用性的增强、修复处理，推荐使用<br>' | |
| '3.保守版(conservative)：如果你担心丢失纹理，担心画风被改变，担心颜色被增强，总之就是各种担心AI会留下浓重的处理痕迹，推荐使用该版本。<br>' | |
| '4.tile越大，越省显存，速度越慢') | |
| iface.launch() | |