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ResNet50??????PyTorch???????? inference ??

????????ResNet50?????????????????????????????????????????????????????????????PyTorch??????ResNet50???????????????

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ResNet50??????????????????????Residual Blocks??????????????????

• ????[1, 3, 224, 224]????????????????
• ???1?[1, 64, 112, 112]
• ?????1?[1, 64, 112, 112]
• ?????ReLU?
• ??????[1, 64, 56, 56]
• ?1?[1, 256, 56, 56]
• ?2?[1, 512, 28, 28]
• ?3?[1, 1024, 14, 14]
• ?4?[1, 2048, 7, 7]
• ??????[1, 2048]
• ?????[1, 1000]

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??? inference ??????????????????PyTorch?????????????????????????????????????

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import cv2
import time
import os
import matplotlib.pyplot as plt
import torch
from torch import nn
import torchvision.models as models
import torchvision.transforms as transforms
savepath = 'vis_resnet50/features_elephant'
if not os.path.exists(savepath):
    os.mkdir(savepath)
def draw_features(width, height, x, savename):
    tic = time.time()
    fig = plt.figure(figsize=(16, 16))
    fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95, wspace=0.05)
    # ??????????
    plt.imshow(x)
    plt.savefig(os.path.join(savepath, savename))
    plt.close()
    toc = time.time()
    print(f"?????{toc - tic:.2f}?")

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• ?????ResNet50?????????????????[1, 3, 224, 224]?
• ??????????PyTorch???????????????
• ????????????????????????????????????????

????????????????ResNet50??????????????????????????

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