hahattpro / crowd_counting_framework (public) (License: Unspecified) (since 2020-12-23) (hash sha1)
backupfrom https://github.com/ttpro1995/crowd_counting_framework
Clone URLs: https://rocketgit.com/user/hahattpro/crowd_counting_framework ssh://rocketgit@ssh.rocketgit.com/user/hahattpro/crowd_counting_framework git://git.rocketgit.com/user/hahattpro/crowd_counting_framework
debug/a-1 develop feature/add_can_adcrowdnet feature/add_context_aware_network feature/attn_can_adcrowd_simple feature/cache_dataloader feature/compact_cnn feature/compare_with_original_count feature/dataloader_not_divide_8 feature/debug_viz feature/documentation feature/improve_density_gen feature/improve_loss_fn feature/loader_full_and_augment feature/refactor-dataflow feature/refactor_ccnn_basecode feature/save_best feature/simple_cometml feature/train_context_aware_network_on_shtA feature/train_dev_test_split hotfix/fix_visualize_data_loader master meow_exp server-training with_apex
List of commits:
Subject Hash Author Date (UTC)
done single sample cee46d309e9bb91ac4185b0e1b74deddefbc8553 Thai Thien 2020-09-06 15:24:39
a ec2103c6617ad84375e5a7a0f3cde3b32ab012a0 Thai Thien 2020-08-23 15:39:51
pred_count d9168903486d7a88c0763a8e93b18d1ed89d2d40 Thai Thien 2020-08-23 15:37:02
density_map_count = gt_density.detach().sum() 015c7ab3a1734c6002065f775f90870b6c5bdbd5 Thai Thien 2020-08-23 15:35:31
no more eval, only one in function 316b330c481224bb4264ddebb3dda2e317c32ac1 Thai Thien 2020-08-23 15:34:21
None type eval 15a12c6dd1a6f828f5e852faecaf2a812dfddce8 Thai Thien 2020-08-23 15:30:17
run experiment on shb truncate 4 3faae2b49ed074fdb96fc20e916fee9eeac4f92f Thai Thien 2020-08-23 15:20:23
evaluatuion shb b80eac051649c36ea1631cc4701e6d1d587d7887 Thai Thien 2020-08-23 09:26:45
fix evaluation shb 51cbe92724973f64cb046f7f49fb1976400827e4 Thai Thien 2020-08-23 09:18:35
typo 1cba17e02cc79ee73c4ad5c9f1faab4913f92b01 Thai Thien 2020-08-23 08:53:21
fix file, mae, mse 245396d814f5d83dff1fd1ecc9fcd403be1805cb Thai Thien 2020-08-23 08:52:16
file name strage stuff caeb9f9608e91cf6a1323d9ae9f4fb215c4dd6ea Thai Thien 2020-08-23 08:44:54
TypeError: can only concatenate str (not "list") to str e8aebcfb782966c11c3ca116b5a9cc254021a73d Thai Thien 2020-08-23 08:41:02
key error 5732100d6aca8e3fea6a4d25270edefbc8148a2a Thai Thien 2020-08-23 08:39:09
fix target fdbda2c6923dd164560448a445cd64ff413fc804 Thai Thien 2020-08-23 08:37:48
test path 06d268f873e6ceea93a8e8741d819a03b324cedb Thai Thien 2020-08-23 08:27:38
a 1d73d926894edbc600db678316b9b24a583c4cb8 Thai Thien 2020-08-23 08:25:58
test set bb1e40fc7806c8bef5e94fbaa54ac9af3b599041 Thai Thien 2020-08-23 08:23:30
remove epoch stuff 2cc6434aa298b6da90b4577ce529f971119b86c7 Thai Thien 2020-08-23 07:53:36
evaluation_shb_CompactCNNV7i_t1 28cf202a306b775967c6e466120b019ae1eb6a4d Thai Thien 2020-08-23 07:49:51
Commit cee46d309e9bb91ac4185b0e1b74deddefbc8553 - done single sample
Author: Thai Thien
Author date (UTC): 2020-09-06 15:24
Committer name: Thai Thien
Committer date (UTC): 2020-09-06 15:24
Parent(s): ec2103c6617ad84375e5a7a0f3cde3b32ab012a0
Signer:
Signing key:
Signing status: N
Tree: d966dbeb5adf2bb71fa04adfba1e11864f433159
File Lines added Lines deleted
dataset_script/jhucrowd_density_map.py 100 0
playground/.ipynb_checkpoints/jhucrowd_label-checkpoint.ipynb 255 0
playground/0003.txt 804 0
playground/jhucrowd_label.ipynb 255 0
File dataset_script/jhucrowd_density_map.py added (mode: 100644) (index 0000000..1f75743)
1 import os
2 import pandas as pd
3 import numpy as np
4 import scipy
5 import scipy.spatial
6 import scipy.ndimage
7 from PIL import Image
8 import h5py
9 from visualize_util import save_density_map
10
11 def load_density_label(label_txt_path):
12 """
13
14 :param label_txt_path: path to txt
15 :return: numpy array, p[sample, a] with a is 0 for x and 1 for y
16 """
17 df = pd.read_csv(label_txt_path, sep=" ", header=None)
18 p = df.to_numpy()
19 return p
20
21
22 def gaussian_filter_density(gt):
23 """
24 generate density map from gt
25 :param gt: matrix same shape as image, where annotation label as 1
26 :return:
27 """
28 print(gt.shape)
29 density = np.zeros(gt.shape, dtype=np.float32)
30 gt_count = np.count_nonzero(gt)
31 if gt_count == 0:
32 return density
33
34 pts = np.array(list(zip(np.nonzero(gt)[1], np.nonzero(gt)[0])))
35 leafsize = 2048
36 # build kdtree
37 pts_copy = pts.copy()
38 tree = scipy.spatial.KDTree(pts_copy, leafsize=leafsize)
39 # query kdtree
40 distances, locations = tree.query(pts, k=4)
41
42 print('generate density...')
43 for i, pt in enumerate(pts):
44 pt2d = np.zeros(gt.shape, dtype=np.float32)
45 pt2d[pt[1], pt[0]] = 1.
46 if gt_count > 1:
47 sigma = (distances[i][1] + distances[i][2] + distances[i][3]) * 0.1
48 else:
49 sigma = np.average(np.array(gt.shape)) / 2. / 2. # case: 1 point
50 density += scipy.ndimage.filters.gaussian_filter(pt2d, sigma, mode='constant')
51 print('done.')
52 return density
53
54 def generate_density_map(img_path, label_path, output_path):
55 """
56
57 :param img_path:
58 :param label_path: txt
59 :param output_path
60 :return:
61 """
62
63 gt = load_density_label(label_path)
64 imgfile = Image.open(img_path).convert('RGB')
65 # imgfile = image.load_img(img_path)
66 img = np.asarray(imgfile)
67
68 # empty matrix zero
69 k = np.zeros((img.shape[0], img.shape[1]))
70 for i in range(0, len(gt)):
71 if int(gt[i][1]) < img.shape[0] and int(gt[i][0]) < img.shape[1]:
72 k[int(gt[i][1]), int(gt[i][0])] = 1
73 k = gaussian_filter_density(k)
74 with h5py.File(output_path, 'w') as hf:
75 hf['density'] = k
76 return output_path
77
78
79 def t_single_density_map():
80 img = "/data/jhu_crowd_v2.0/val/images/0003.jpg"
81 label = "/data/jhu_crowd_v2.0/val/gt/0003.txt"
82 out_path = "/data/jhu_crowd_v2.0/val/unittest/0003.txt"
83 out = generate_density_map(img, label, out_path)
84 print(out)
85
86
87 def print_density_map(density_path, density_img_out):
88 gt_file = h5py.File(density_path, 'r')
89 target = np.asarray(gt_file['density'])
90 save_density_map(target, density_img_out)
91 print("done print ", density_img_out)
92
93 if __name__ == "__main__":
94 # t_single_density_map()
95 print_density_map("/data/jhu_crowd_v2.0/val/unittest/0003.h5", "/data/jhu_crowd_v2.0/val/unittest/0003.png")
96
97 # ROOT = "/data/jhu_crowd_v2.0/val"
98 # images_folder = os.path.join(ROOT, "images")
99 # gt_path_folder = os.path.join(ROOT, "gt")
100
File playground/.ipynb_checkpoints/jhucrowd_label-checkpoint.ipynb added (mode: 100644) (index 0000000..5ad7071)
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