hahattpro / crowd_counting_framework (public) (License: Unspecified) (since 2020-12-23) (hash sha1)
backupfrom https://github.com/ttpro1995/crowd_counting_framework
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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)
PACNN (TODO: test this) 44d5ae7ec57c760fb4f105dd3e3492148a0cc075 Thai Thien 2020-02-02 03:40:26
add data path 80134de767d0137a663f343e4606bafc57a1bc1f Thai Thien 2020-02-02 03:38:21
test if ShanghaiTech datapath is correct 97ee84944a4393ec3732879b24f614826f8e7798 Thai Thien 2020-02-01 03:57:31
refactor and test ShanghaiTech datapath 9542ebc00f257edc38690180b7a4353794be4019 Thai Thien 2020-02-01 03:53:49
fix the unzip flow b53c5989935335377eb6a88c942713d3eccc5df7 Thai Thien 2020-02-01 03:53:13
data_script run seem ok 67420c08fc1c10a66404d3698994865726a106cd Thai Thien 2020-02-01 03:33:18
add perspective 642d6fff8c9f31e510fda85a7fb631fb855d8a6d Thai Thien 2019-10-06 16:54:44
fix padding with p 86c2fa07822d956a34b3b37e14da485a4249f01b Thai Thien 2019-10-06 02:52:58
pacnn perspective loss fb673e38a5f24ae9004fe2b7b93c88991e0c2304 Thai Thien 2019-10-06 01:38:28
data_flow shanghaitech_pacnn_with_perspective seem working 91d350a06f358e03223966297d124daee94123d0 Thai Thien 2019-10-06 01:31:11
multiscale loss and final loss only mode c65dd0e74ad28503821e5c8651a3b47b4a0c7c64 Thai Thien 2019-10-05 15:58:19
wip : perspective map eac63f2671dc5b064753acc4f40bf0f9f216ad2a Thai Thien 2019-10-04 16:26:56
shell script f2106e700b6f6174d4dd276f25ec6f3d9ff239bb thient 2019-10-04 07:42:51
WIP 42c7c8e1d772fbbda61a4bdf9e329f74e1efb600 tthien 2019-10-03 17:52:47
add readme 580cf43d1edddd67b1f6a2c57fdd5cee3dba925c Thai Thien 2019-10-02 17:44:49
update script, debug ddb68b95389be1c1d398118677dd227a8bb2b70b Thai Thien 2019-10-02 15:52:31
add d (output density map) to loss function) a0c71bf4bf2ab7393d60b06a84db8dfbbfb1a6c2 tthien 2019-09-30 16:32:39
fix the args, add save interval for model, so we don't save them all 9fdf9daa2ac4bd12b7b62521d81e520db0debd01 tthien 2019-09-30 16:30:00
meow 1ad19a22a310992e27a26471feeb37375124d075 tthien 2019-09-29 18:25:43
fix pacnn perspective map 453ece3ccb818889ba895bfc4285f7905d33cba5 Thai Thien 2019-09-25 17:20:33
Commit 44d5ae7ec57c760fb4f105dd3e3492148a0cc075 - PACNN (TODO: test this)
Author: Thai Thien
Author date (UTC): 2020-02-02 03:40
Committer name: Thai Thien
Committer date (UTC): 2020-02-02 03:40
Parent(s): 5cc333d2996b09eb0d69eee4daa2baa51a21aa11
Signing key:
Tree: 24300342f7b1a9f6257d34fd05513d081c0c25cb
File Lines added Lines deleted
models/pacnn.py 3 5
File models/pacnn.py changed (mode: 100644) (index 0336b5c..58213af)
... ... class PACNNWithPerspectiveMap(nn.Module):
73 73 pespective_w_s = self.perspective_11(self.perspective_net(x)) pespective_w_s = self.perspective_11(self.perspective_net(x))
74 74 pespective_w = self.up_perspective(pespective_w_s) pespective_w = self.up_perspective(pespective_w_s)
75 75
76
77 # TODO: code more here
78 76 upde3 = self.up23(de3) upde3 = self.up23(de3)
79 77 pad_3_0 = de2.size()[2] - upde3.size()[2] pad_3_0 = de2.size()[2] - upde3.size()[2]
80 78 pad_3_1 = de2.size()[3] - upde3.size()[3] pad_3_1 = de2.size()[3] - upde3.size()[3]
 
... ... def parameter_count_test():
133 131 print(sum_of_part) print(sum_of_part)
134 132
135 133 if __name__ == "__main__": if __name__ == "__main__":
136 parameter_count_test()
137 # net = PACNN()
138 # print(net.de1net)
134 # parameter_count_test()
135 net = PACNN()
136 print(net.de1net)
139 137 # img = torch.rand(1, 3, 320, 320) # img = torch.rand(1, 3, 320, 320)
140 138 # de1, de2, de3 = net(img) # de1, de2, de3 = net(img)
141 139 # print(de1.size()) # print(de1.size())
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