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hahattpro / crowd_counting_framework (public) (License: Unspecified) (since 2020-12-23) (hash sha1)

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List of commits:

Subject	Hash	Author	Date (UTC)
update documentation	feaaa4095d89e99f71f0684eec302d01e421708d	Thai Thien	2020-04-30 15:35:38
change gpu	c7c6aa29ccee5736c2d4cb290c2ff71c6d897d57	Thai Thien	2020-04-30 12:31:11
reduce batch size	2b2820095211e117c6d02236ef85adb89b70098f	Thai Thien	2020-04-30 12:28:32
forget .to(device)	a641d5cdf82eb89c9034253785e80dd920c1f5d6	Thai Thien	2020-04-30 12:25:22
reduce batch size of shb keepfull	044f6785fedcf442def0fdb24109413a79274289	Thai Thien	2020-04-30 12:20:21
ccnn v7 with ssim loss	40079e5354eef95e0e89cf23a7f2025ee362e232	Thai Thien	2020-04-30 12:16:19
local	1d4e08754bd493e76cf09076de7c76adf1a30a0a	Thai Thien	2020-04-30 12:10:15
mse-ssim loss function	052de7c879bff7690a7cfc1905c8376bf8605c45	Thai Thien	2020-04-30 11:41:24
delete misinformation note	ca07533d585def04eec086685f2e72eacc330ddc	Thai Thien	2020-04-29 16:59:47
typo	3505077301af5349665f12121862db2512ad450a	Thai Thien	2020-04-29 16:59:03
change, adapt, survive	6755c8375302af2146cb63adc967631d53a7b1c8	Thai Thien	2020-04-29 16:48:10
gpu	861ec0d41cea2eec359c6ddfe207e1ed6b583369	Thai Thien	2020-04-28 18:08:11
ccnn_v7_t4	a84f63e64fe8b31fe22c94d383de5ed4e1a27fe4	Thai Thien	2020-04-28 18:07:33
2500	d37516f53d21f3dfc05143ba5ffda80fc5a07825	Thai Thien	2020-04-28 17:56:57
change max epoch	246ae30e6dd2b4a15b7dc70a3dc05592ac1c48f2	Thai Thien	2020-04-28 17:55:23
h1 t3 h1 t4	fbcd13dd240e06a982a1ce48f27cd1d542a26b63	Thai Thien	2020-04-28 17:53:06
h1	96204cb5262500020371637741131d24e3fa91d0	Thai Thien	2020-04-27 17:35:51
typo	adfb213c2564bc90b8b69811469534b004808644	Thai Thien	2020-04-27 17:17:58
batch size 8 for shb	c90fa9a5d725a1ef0d29ed23f947ee05b9aa7894	Thai Thien	2020-04-27 17:10:34
change proxy	30cd53782eb17b416c471502f1e6c6e9975a644b	Thai Thien	2020-04-27 17:06:28

Commit feaaa4095d89e99f71f0684eec302d01e421708d - update documentation
Author: Thai Thien
Author date (UTC): 2020-04-30 15:35
Committer name: Thai Thien
Committer date (UTC): 2020-04-30 15:35
Parent(s): c7c6aa29ccee5736c2d4cb290c2ff71c6d897d57
Signing key:
Tree: 66ec5e85c09d518ff3c806ba1a5b804c249b19d4

File	Lines added	Lines deleted
README.md	16	1
dataset_script/README.md	9	1
dataset_script/download_kaggle_crowd_dataset.sh	2	2

File README.md changed (mode: 100644) (index c3455df..bfe4add)
	1		# WORK IN PROGRESS
	2		I am trying to publish a paper for graduating. I really need to publish.
	3
	4		<b> Please do not copy my work and my ideal to use as your own. </b> I really need to publish (a) paper(s), I hope you understand.
	5		<br><br>
	6
	7		However, you can use my framework as starter code for your own work, or use my re-implementation of other works.
	8
	9
1	10	### Environment	### Environment
2	11	```	```
3	12	conda create -n env python=3.7 anaconda	conda create -n env python=3.7 anaconda

...	...	sudo chown -R tt /data/
30	39	When you use comet.ml	When you use comet.ml
31	40	```shell script	```shell script
32	41	conda install -c comet_ml comet_ml	conda install -c comet_ml comet_ml
33		```
	42		```
	43
	44		""
	45		TODO:
	46		https://github.com/kornia/kornia/blob/master/kornia/losses/ssim.py
	47
	48		add ssim from here

File dataset_script/README.md changed (mode: 100644) (index c7aafda..0900f05)
1	1	# All thing in this folder handle data	# All thing in this folder handle data
2	2
	3		The dataset, which is publicly available on the internet, belong to their original author. I only re-upload and process the dataset to use for my own project. I make it publicly available so I might save some of your time.
	4
	5		Shanghaitech dataset [Single-Image Crowd Counting via Multi-Column Convolutional Neural Network](https://pdfs.semanticscholar.org/7ca4/bcfb186958bafb1bb9512c40a9c54721c9fc.pdf)
	6
	7		UCF-CC-50 dataset [Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images](http://openaccess.thecvf.com/content_cvpr_2013/papers/Idrees_Multi-source_Multi-scale_Counting_2013_CVPR_paper.pdf)
	8
3	9	### Kaggle dataset	### Kaggle dataset
4	10
5		First, install https://anaconda.org/conda-forge/kaggle
	11		You will need a Kaggle account, and a working installation of Conda on your machine.
	12
	13		First, install [Kaggle](https://anaconda.org/conda-forge/kaggle) package by conda
6	14	```bash	```bash
7	15	conda install -c conda-forge kaggle	conda install -c conda-forge kaggle
8	16	```	```

File dataset_script/download_kaggle_crowd_dataset.sh changed (mode: 100644) (index ce48f8d..46c84d5)
1	1	#kaggle datasets download ucf-cc-50-with-people-density-map	#kaggle datasets download ucf-cc-50-with-people-density-map
2		kaggle datasets download shanghaitech-with-people-density-map
3		kaggle datasets download perspective-shanghaitech
	2		kaggle datasets download tthien/shanghaitech-with-people-density-map
	3		kaggle datasets download tthien/perspective-shanghaitech

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