/visualize_util.py (0190315ac06c5ba26ba8777fec0d3bef334d1da3) (910 bytes) (mode 100644) (type blob)

import glob
import PIL.Image as Image
from matplotlib import pyplot as plt
from matplotlib import cm as CM
import os
import numpy as np

from PIL import Image


def save_density_map(density_map, name):
    plt.figure(dpi=600)
    plt.axis('off')
    plt.margins(0, 0)
    plt.imshow(density_map, cmap=CM.jet)
    plt.savefig(name, dpi=600, bbox_inches='tight', pad_inches=0)
    plt.close()

def save_density_map_with_colorrange(density_map, name, vmin, vmax):
    plt.figure(dpi=600)
    plt.axis('off')
    plt.margins(0, 0)
    plt.imshow(density_map, cmap=CM.jet)
    plt.clim(vmin, vmax)
    plt.savefig(name, dpi=600, bbox_inches='tight', pad_inches=0)
    plt.close()

def save_img(imgnp, name):
    # plt.imshow(imgnp[0].permute(1, 2, 0).numpy())
    plt.imsave(name, imgnp[0].permute(1, 2, 0).numpy())
    # plt.show()
    # im = Image.fromarray(imgnp[0].permute(1, 2, 0).numpy())
    # im.save(name)


Mode Type Size Ref File
100644 blob 61 169fe2b7d512a59cfedf86ddb7ed040173c7434d .gitignore
100644 blob 419 b2f2bf709bdb475a4d2cf349bcfc4da53ff7870d README.md
100644 blob 2883 2e74c0766f12afff56a0b1621055a2794f64418a args_util.py
040000 tree - 5e9d7f0e1fd3a9e4d5a37f3d6de0c3ecd3125af8 backup_notebook
040000 tree - 55d1d196f5b6ed4bfc1e8a715df1cfff1dd18117 bug
100644 blob 1775 1165f1aba0814b448a3595a32bd74f1967509509 crowd_counting_error_metrics.py
100644 blob 11956 a3f3d3c1877596d79b75d7943ac7bf7e3879d752 data_flow.py
040000 tree - 17c9c74641b7acc37008a7f940a62323dd5b2b6b data_util
040000 tree - 2a46ff24b8b8997b4ca07c18e2326cb3c35dc5a0 dataset_script
100644 blob 4460 9b254c348a3453f4df2c3ccbf21fb175a16852de eval_context_aware_network.py
100644 blob 428 35cc7bfe48a4ed8dc56635fd3a6763612d8af771 evaluator.py
100644 blob 2718 b09b84e8b761137654ba6904669799c4866554b3 hard_code_variable.py
100644 blob 15300 cb90faba0bd4a45f2606a1e60975ed05bfacdb07 main_pacnn.py
100644 blob 2760 3c2d5ba1c81ef2770ad216c566e268f4ece17262 main_shanghaitech.py
100644 blob 2683 29189260c1a2c03c8e59cd0b4bd61df19d5ce098 main_ucfcc50.py
100644 blob 815 eeb34682e8425776dc9e70326a77c2333ae10e5c model_util.py
040000 tree - 4d8049aed49b47d71d677d00369c5333bd9451e9 models
040000 tree - d1c13a0fa59c995bbc5c766ea807108aabbc41a8 playground
040000 tree - 970ac54d8293aed6667e016f2245547f3a5449c3 pytorch_ssim
040000 tree - cedc468471f9743100c7f608acc15c89be992a6c train_script
100644 blob 4420 09c9f3bf867542ac93a1e19546f790feab8c53bd visualize_data_loader.py
100644 blob 910 0190315ac06c5ba26ba8777fec0d3bef334d1da3 visualize_util.py
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