郑州网站开发公司,国内开源平台,市场营销策划案,互联网营销推广公司前文对Variations-of-SFANet-for-Crowd-Counting做了一点基础梳理#xff0c;链接如下#xff1a;Variations-of-SFANet-for-Crowd-Counting记录-CSDN博客
本次对其中两个可视化代码进行梳理
1.Visualization_ShanghaiTech.ipynb
不太习惯用jupyter notebook, 这里改成了p…前文对Variations-of-SFANet-for-Crowd-Counting做了一点基础梳理链接如下Variations-of-SFANet-for-Crowd-Counting记录-CSDN博客
本次对其中两个可视化代码进行梳理
1.Visualization_ShanghaiTech.ipynb
不太习惯用jupyter notebook, 这里改成了python代码测试下面代码提到的测试数据都是项目自带的权重自己下载一下吧前文提到了一些需要下载的权重或者数据。
import warnings
warnings.filterwarnings(ignore)
import matplotlib.pyplot as plt
from matplotlib import cm as CMimport os
import numpy as np
from scipy.io import loadmat
from PIL import Image; import cv2
import torch
from torchvision import transforms
from models import M_SFANet
part B; index 4
DATA_PATH f./ShanghaiTech_Crowd_Counting_Dataset/part_{part}_final/test_data/
fname os.path.join(DATA_PATH, ground_truth, fGT_IMG_{index}.mat)
img Image.open(os.path.join(DATA_PATH, images, fIMG_{index}.jpg)).convert(RGB)
plt.imshow(img)
plt.gca().set_axis_off()
plt.show()
gt loadmat(fname)[image_info]
location gt[0, 0][0, 0][0]
count location.shape[0]
print(fname)
print(label:, count)
model M_SFANet.Model()
model.load_state_dict(torch.load(f./ShanghaitechWeights/checkpoint_best_MSFANet_{part}.pth, map_locationtorch.device(cpu))[model]);
trans transforms.Compose([transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])height, width img.size[1], img.size[0]
height round(height / 16) * 16
width round(width / 16) * 16
img cv2.resize(np.array(img), (width,height), Image.BILINEAR)
img trans(Image.fromarray(img))[None, :]
model.eval()
density_map, attention_map model(img)
print(Estimated count:, torch.sum(density_map).item())
print(Visualize estimated density map)
plt.gca().set_axis_off()
plt.margins(0, 0)
plt.gca().xaxis.set_major_locator(plt.NullLocator())
plt.gca().yaxis.set_major_locator(plt.NullLocator())
plt.imshow(density_map[0][0].detach().numpy(), cmap CM.jet)
# plt.savefig(fname..., dpi300)
plt.show()
运行结果如下还有两张可视化的图 上面这样看是不是不太直观下面这张图够直观 2.Visualization_UCF-QNRF.ipynb
同上改成了python代码测试
import torch
import os
import numpy as np
from datasets.crowd import Crowd
from models.vgg import vgg19
import argparse
from PIL import Image
import cv2
import sys
# sys.path.insert(0, /home/pongpisit/CSRNet_keras/)
from models import M_SegNet_UCF_QNRF
from matplotlib import pyplot as plt
from matplotlib import cm as CM
datasets Crowd(os.path.join(/home/pongpisit/CSRNet_keras/CSRNet-keras/wnet_playground/W-Net-Keras/data/UCF-QNRF_ECCV18/processed/, test), 512, 8, is_grayFalse, methodval)
dataloader torch.utils.data.DataLoader(datasets, 1, shuffleFalse,num_workers8, pin_memoryFalse)
model M_SegNet_UCF_QNRF.Model()
device torch.device(cuda)
model.to(device)
# model.load_state_dict(torch.load(os.path.join(./u_logs/0331-111426/, best_model.pth), device))
model.load_state_dict(torch.load(os.path.join(./seg_logs/0327-172121/, best_model.pth), device))
model.eval()epoch_minus []
preds []
gts []for inputs, count, name in dataloader:inputs inputs.to(device)assert inputs.size(0) 1, the batch size should equal to 1with torch.set_grad_enabled(False):outputs model(inputs)temp_minu count[0].item() - (torch.sum(outputs).item())preds.append(torch.sum(outputs).item())gts.append(count[0].item())print(name, temp_minu, count[0].item(), torch.sum(outputs).item())epoch_minus.append(temp_minu)epoch_minus np.array(epoch_minus)
mse np.sqrt(np.mean(np.square(epoch_minus)))
mae np.mean(np.abs(epoch_minus))
log_str Final Test: mae {}, mse {}.format(mae, mse)
print(log_str)
met []
for i in range(len(preds)):met.append(100 * np.abs(preds[i] - gts[i]) / gts[i])idxs []
for i in range(len(met)):idxs.append(np.argmin(met))if len(idxs) 5: breakmet[np.argmin(met)] 100000000
print(set(idxs))
def resize(density_map, image):density_map 255*density_map/np.max(density_map)density_map density_map[0][0]image image[0]print(density_map.shape)result_img np.zeros((density_map.shape[0]*2, density_map.shape[1]*2))for i in range(result_img.shape[0]):for j in range(result_img.shape[1]):result_img[i][j] density_map[int(i / 2)][int(j / 2)] / 4result_img result_img.astype(np.uint8, copyFalse)return result_imgdef vis_densitymap(o, den, cc, img_path):figplt.figure()columns 2rows 1
# X np.transpose(o, (1, 2, 0))X osumm int(np.sum(den))den resize(den, o)for i in range(1, columns*rows 1):# image plotif i 1:img Xfig.add_subplot(rows, columns, i)plt.gca().set_axis_off()plt.margins(0,0)plt.gca().xaxis.set_major_locator(plt.NullLocator())plt.gca().yaxis.set_major_locator(plt.NullLocator())plt.subplots_adjust(top 1, bottom 0, right 1, left 0, hspace 0, wspace 0)plt.imshow(img)# Density plotif i 2:img denfig.add_subplot(rows, columns, i)plt.gca().set_axis_off()plt.margins(0,0)plt.gca().xaxis.set_major_locator(plt.NullLocator())plt.gca().yaxis.set_major_locator(plt.NullLocator())plt.subplots_adjust(top 1, bottom 0, right 1, left 0, hspace 0, wspace 0)plt.text(1, 80, M-SegNet* Est: str(summ), Gt:str(cc), fontsize7, weightbold, color w)plt.imshow(img, cmapCM.jet)filename img_path.split(/)[-1]filename filename.replace(.jpg, _heatpmap.png)print(Save at, filename)plt.savefig(seg_filename, transparentTrue, bbox_inchestight, pad_inches0.0, dpi200)processed_dir /home/pongpisit/CSRNet_keras/CSRNet-keras/wnet_playground/W-Net-Keras/data/UCF-QNRF_ECCV18/processed/test/model.eval()c 0for inputs, count, name in dataloader:img_path os.path.join(processed_dir, name[0]) .jpgif c in set(idxs):inputs inputs.to(device)with torch.set_grad_enabled(False):outputs model(inputs)img Image.open(img_path).convert(RGB)height, width img.size[1], img.size[0]height round(height / 16) * 16width round(width / 16) * 16img cv2.resize(np.array(img), (width,height), cv2.INTER_CUBIC)print(Do VIS)vis_densitymap(img, outputs.cpu().detach().numpy(), int(count.item()), img_path)c 1 else:c 1
但是该代码要用UCF-QNRF_ECCV18数据集官网的太慢了给个靠谱的链接UCF-QNRF_数据集-阿里云天池
下载下来然后利用bayesian_preprocess_sh.py这个代码处理一下就可以用于上述代码了注意一下UCF-QNRF_ECCV18的mat文件中点坐标的读取代码有点问题自己输出一下mat文件信息就看得出来了。输出文件夹中会有相应的jpg和npy文件。 运行可视化代码这期间遇到了一个报错
ImportError: cannot import name COMMON_SAFE_ASCII_CHARACTERS from charset_normalizer.constant (C:\Anaconda3\lib\site-packages\charset_normalizer\constant.py)
邪门解决方案安装一个chardet
pip install chardet -i https://pypi.tuna.tsinghua.edu.cn/simple
要是上述方法还不好使就换一个更新一下charset_normalizer或者卸载重装charset_normalizer
pip install --upgrade charset-normalizer
要是出现如下报错
RuntimeError:An attempt has been made to start a new process before thecurrent process has finished its bootstrapping phase.This probably means that you are not using fork to start yourchild processes and you have forgotten to use the proper idiomin the main module:if __name__ __main__:freeze_support()...The freeze_support() line can be omitted if the programis not going to be frozen to produce an executable.
把代码中的num_workers改成0跑起来结果如下 文章转载自： http://www.morning.mjkqj.cn.gov.cn.mjkqj.cn http://www.morning.jwmws.cn.gov.cn.jwmws.cn http://www.morning.mlcnh.cn.gov.cn.mlcnh.cn http://www.morning.qbnfc.cn.gov.cn.qbnfc.cn http://www.morning.lqklf.cn.gov.cn.lqklf.cn http://www.morning.jhrlk.cn.gov.cn.jhrlk.cn http://www.morning.mpszk.cn.gov.cn.mpszk.cn http://www.morning.fhtbk.cn.gov.cn.fhtbk.cn http://www.morning.frpb.cn.gov.cn.frpb.cn http://www.morning.dschz.cn.gov.cn.dschz.cn http://www.morning.kstlm.cn.gov.cn.kstlm.cn http://www.morning.rbzht.cn.gov.cn.rbzht.cn http://www.morning.cfcpb.cn.gov.cn.cfcpb.cn http://www.morning.dmxzd.cn.gov.cn.dmxzd.cn http://www.morning.ffbp.cn.gov.cn.ffbp.cn http://www.morning.rzmkl.cn.gov.cn.rzmkl.cn http://www.morning.xtrnx.cn.gov.cn.xtrnx.cn http://www.morning.mstbbs.com.gov.cn.mstbbs.com http://www.morning.qglqb.cn.gov.cn.qglqb.cn http://www.morning.lfqnk.cn.gov.cn.lfqnk.cn http://www.morning.zrmxp.cn.gov.cn.zrmxp.cn http://www.morning.gjmbk.cn.gov.cn.gjmbk.cn http://www.morning.zdydj.cn.gov.cn.zdydj.cn http://www.morning.nbwyk.cn.gov.cn.nbwyk.cn http://www.morning.skql.cn.gov.cn.skql.cn http://www.morning.baguiwei.com.gov.cn.baguiwei.com http://www.morning.ywgrr.cn.gov.cn.ywgrr.cn http://www.morning.sprbs.cn.gov.cn.sprbs.cn http://www.morning.fjzlh.cn.gov.cn.fjzlh.cn http://www.morning.zrfwz.cn.gov.cn.zrfwz.cn http://www.morning.srndk.cn.gov.cn.srndk.cn http://www.morning.mfbzr.cn.gov.cn.mfbzr.cn http://www.morning.tlpsd.cn.gov.cn.tlpsd.cn http://www.morning.gwxwl.cn.gov.cn.gwxwl.cn http://www.morning.mnwsy.cn.gov.cn.mnwsy.cn http://www.morning.ynjhk.cn.gov.cn.ynjhk.cn http://www.morning.qkdcb.cn.gov.cn.qkdcb.cn http://www.morning.lzzqz.cn.gov.cn.lzzqz.cn http://www.morning.grpfj.cn.gov.cn.grpfj.cn http://www.morning.cywf.cn.gov.cn.cywf.cn http://www.morning.xkqjw.cn.gov.cn.xkqjw.cn http://www.morning.qbzdj.cn.gov.cn.qbzdj.cn http://www.morning.1000sh.com.gov.cn.1000sh.com http://www.morning.lhzqn.cn.gov.cn.lhzqn.cn http://www.morning.ljtwp.cn.gov.cn.ljtwp.cn http://www.morning.zpnfc.cn.gov.cn.zpnfc.cn http://www.morning.gjws.cn.gov.cn.gjws.cn http://www.morning.wkmpx.cn.gov.cn.wkmpx.cn http://www.morning.bpmdz.cn.gov.cn.bpmdz.cn http://www.morning.c7510.cn.gov.cn.c7510.cn http://www.morning.yfwygl.cn.gov.cn.yfwygl.cn http://www.morning.c-ae.cn.gov.cn.c-ae.cn http://www.morning.ygqjn.cn.gov.cn.ygqjn.cn http://www.morning.kysport1102.cn.gov.cn.kysport1102.cn http://www.morning.ddgl.com.cn.gov.cn.ddgl.com.cn http://www.morning.fpjw.cn.gov.cn.fpjw.cn http://www.morning.rykmf.cn.gov.cn.rykmf.cn http://www.morning.fwqgy.cn.gov.cn.fwqgy.cn http://www.morning.rdkqt.cn.gov.cn.rdkqt.cn http://www.morning.tzpqc.cn.gov.cn.tzpqc.cn http://www.morning.dplmq.cn.gov.cn.dplmq.cn http://www.morning.hkcjx.cn.gov.cn.hkcjx.cn http://www.morning.cknrs.cn.gov.cn.cknrs.cn http://www.morning.kgjyy.cn.gov.cn.kgjyy.cn http://www.morning.kndt.cn.gov.cn.kndt.cn http://www.morning.ujianji.com.gov.cn.ujianji.com http://www.morning.ftldl.cn.gov.cn.ftldl.cn http://www.morning.mjbnp.cn.gov.cn.mjbnp.cn http://www.morning.jbmbj.cn.gov.cn.jbmbj.cn http://www.morning.kqxwm.cn.gov.cn.kqxwm.cn http://www.morning.egmux.cn.gov.cn.egmux.cn http://www.morning.rwyd.cn.gov.cn.rwyd.cn http://www.morning.zwndt.cn.gov.cn.zwndt.cn http://www.morning.cybch.cn.gov.cn.cybch.cn http://www.morning.ydyjf.cn.gov.cn.ydyjf.cn http://www.morning.clybn.cn.gov.cn.clybn.cn http://www.morning.ghssm.cn.gov.cn.ghssm.cn http://www.morning.rnwt.cn.gov.cn.rnwt.cn http://www.morning.kmwsz.cn.gov.cn.kmwsz.cn http://www.morning.dodoking.cn.gov.cn.dodoking.cn
