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PyTorch實現(xiàn)ResNet50、ResNet101和ResNet152示例_python_腳本之家

model = ResNet50() print(model) input = torch.randn(1, 3, 224, 224) out = model(input) print(out.shape)以上這篇PyTorch實現(xiàn)ResNet50、ResNet101和ResNet152示例就是小編分享給大家的全部內(nèi)容了,希望能給大家一個參考,也希望大家多多支持腳本之家。您可能感興趣的文章
www.dbjr.com.cn/article/1783...htm 2025-5-28

PyTorch 之 強大的 hub 模塊和搭建神經(jīng)網(wǎng)絡進行氣溫預測_python_腳本之...

# 'deeplabv3_resnet101', # 'densenet121', # 'densenet161', # 'densenet169', # 'densenet201', # 'fcn_resnet101', # 'googlenet', # 'inception_v3', # 'mobilenet_v2', # 'resnet101', # 'resnet152', # 'resnet18', # 'resnet34', # 'resnet50', # 'resnext101_32x8d', #...
www.dbjr.com.cn/article/2784...htm 2023-3-20

pytorch 一行代碼查看網(wǎng)絡參數(shù)總量的實現(xiàn)_python_腳本之家

fromtorchstatimportstat fromtorchvision.modelsimportresnet50, resnet101, resnet152, resnext101_32x8d model=resnet50() stat(model, (3,224,224)) 打印信息如下: 以上為個人經(jīng)驗,希望能給大家一個參考,也希望大家多多支持腳本之家。如有錯誤或未考慮完全的地方,望不吝賜教。
www.dbjr.com.cn/article/2120...htm 2025-6-5

Python+AI實現(xiàn)給老照片上色_python_腳本之家

ColorizeArtistic_gen.pth:在有趣的細節(jié)和活力方面實現(xiàn)了最高質(zhì)量的圖像著色效果,該模型在 UNet 上使用 resnet34 為主干,通過 NoGAN 進行了 5 次評論家預訓練/GAN 循環(huán)重復訓練 ColorizeStable_gen.pth:在風景和肖像方面取得了最佳效果,該模型在 UNet 上使用 resnet101 為主干,通過 NoGAN 進行了 3 次評論家...
www.dbjr.com.cn/article/2514...htm 2025-6-1

Python中CLIP多模態(tài)模型的庫的實現(xiàn)_python_腳本之家

"RN50"、"RN101":基于 ResNet 4. 文本編碼 1 2 3 4 5 text=["a photo of a banana","a dog","a car"] tokens=clip.tokenize(text).to(device) with torch.no_grad(): text_features=model.encode_text(tokens) 5. 圖像編碼 1 2
www.dbjr.com.cn/python/340582r...htm 2025-5-30

使用PyTorch實現(xiàn)手寫數(shù)字識別功能_python_腳本之家

您可能感興趣的文章: pytorch如何利用ResNet18進行手寫數(shù)字識別 PyTorch實現(xiàn)MNIST數(shù)據(jù)集手寫數(shù)字識別詳情 PyTorch實現(xiàn)手寫數(shù)字的識別入門小白教程 PyTorch實現(xiàn)手寫數(shù)字識別的示例代碼 PyTorch簡單手寫數(shù)字識別的實現(xiàn)過程微信公眾號搜索 “ 腳本之家” ,選擇關注 程序猿的那些事、送書等活動等著你 原文鏈接:https://juejin....
www.dbjr.com.cn/python/3382891...htm 2025-6-5

pytorch使用horovod多gpu訓練的實現(xiàn)_python_腳本之家

model = models.resnet50() # By default, Adasum doesn't need scaling up learning rate. # For sum/average with gradient Accumulation: scale learning rate by batches_per_allreduce lr_scaler = args.batches_per_allreduce * hvd.size() if not args.use_adasum else 1 if args.cuda: # Move ...
www.dbjr.com.cn/article/1952...htm 2025-6-1

教你如何用Pytorch搭建數(shù)英混合驗證碼圖片識別模型_python_腳本之家

class CBAtten_Res(nn.Module): ''' func:channel attention + spatial attention + resnet parameters: in_channels: input的通道數(shù), input.size = (batch,in_channels,w,h) if batch_first else (in_channels,batch,,w,h); out_channels: 輸出的通道數(shù) kernel_size: 默認3, 可選[3,5,7] stride:...
www.dbjr.com.cn/python/319635a...htm 2025-6-8

pytorch之inception_v3的實現(xiàn)案例_python_腳本之家

if model_name == "resnet": """ Resnet18 """ model_ft = models.resnet18(pretrained=use_pretrained) set_parameter_requires_grad(model_ft, feature_extract) num_ftrs = model_ft.fc.in_features model_ft.fc = nn.Linear(num_ftrs, num_classes) input_size = 224 elif model_name == "...
www.dbjr.com.cn/article/1779...htm 2025-5-28

在Pytorch中使用Mask R-CNN進行實例分割操作_python_腳本之家

model = torchvision.models.detection.maskrcnn_resnet50_fpn(pretrained=True) model.eval() img = Image.open(image_path) transform = T.Compose([T.ToTensor()]) img = transform(img) if gpu: model.cuda() img = img.cuda() else: model.cpu() img = img.cpu() start_time = time.time()...
www.dbjr.com.cn/article/1894...htm 2025-5-25