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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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List of commits:

Subject	Hash	Author	Date (UTC)
add load_data_shanghaitech_keepfull_and_crop	5af55c5b483263683db80bcf4b870bfbb241d668	Thai Thien	2020-03-12 16:19:19
change on how it log epoch	adcb2aa917f02d4b5d567a9b70f08ec519f896d1	Thai Thien	2020-03-11 17:32:35
fix the milestone	4e8c048ff8db59cbedc819e4df2a48094568fc2c	Thai Thien	2020-03-11 17:10:03
add COMET_ML_API	7fbec715d751544bcdafb34a686602839a2696de	Thai Thien	2020-03-11 17:04:19
fix script name	631c37c068377706ae2cad4513baeea7e62ae0b5	Thai Thien	2020-03-11 16:59:24
intergrate comet ml into compact cnn	058e90a617acb76a7788e6a5d44f52563342490b	Thai Thien	2020-03-11 16:57:17
something ?!	fff52ff87af2a90452384a01bd6d6e6c4b91654e	Thai Thien	2020-03-11 15:55:04
DilatedCCNNv2	75d2989232a8a68eba9b4920ab2374ac28438e0e	Thai Thien	2020-03-10 05:11:12
fix script for ccnn_v2_t1_c2	57928056d13bc9b1f9b11e14dd305005a3a5aeea	Thai Thien	2020-03-10 04:56:33
fix trash code	33c406b13b5d45527b05dfb7f4281c3966c6471e	Thai Thien	2020-03-10 04:49:52
repair dir in config	baf522825f906a3d1fc5524f42a80da33d059640	Thai Thien	2020-03-10 04:45:11
v3 t1 c2	2d4727f47f4262833dca2087fb9e48f0d117e334	Thai Thien	2020-03-10 04:29:23
dilated ccnn v1 t1	7807d7a979353fa84d0b7319820386e93dbe5cc4	Thai Thien	2020-03-09 17:20:58
new ccnn	44a669c1f918be9d74313f29a5dbbc876c29f2fc	Thai Thien	2020-03-09 17:16:49
fix script	aa331331b12e5b454d372a550524b30a4bebe706	Thai Thien	2020-03-07 18:32:06
try reproduct ccnn with keepfull and lr 1e-5	814c520cbd1bb2d7fd50d2a8d3579d43da79fe60	Thai Thien	2020-03-07 18:30:42
my simple v4 with addition deform cnn at the end	5392aaf6c14fdd910f52096dbb921bed7470c4f7	Thai Thien	2020-03-07 18:15:22
fix the scheduler	77e6737a040f5aa5745b8a8830f5bec12322b10f	Thai Thien	2020-03-07 17:46:02
t4 lr 1e-5	acd41ed30c95f63e01a05a6d9929410637852d9e	Thai Thien	2020-03-06 19:41:49
no more lr scheduler	7289adb41de7807258eb8c29e6108fa65f59525a	Thai Thien	2020-03-06 19:35:49

Commit 5af55c5b483263683db80bcf4b870bfbb241d668 - add load_data_shanghaitech_keepfull_and_crop
Author: Thai Thien
Author date (UTC): 2020-03-12 16:19
Committer name: Thai Thien
Committer date (UTC): 2020-03-12 16:19
Parent(s): adcb2aa917f02d4b5d567a9b70f08ec519f896d1
Signing key:
Tree: 75c05b5720a392e129e7dbdaaf7756871c4edc00

File	Lines added	Lines deleted
data_flow.py	44	2

File data_flow.py changed (mode: 100644) (index 7763ae4..1260368)
...	...	def load_data_shanghaitech_keepfull(img_path, train=True):
147	147	return img, target1	return img, target1
148	148
149	149
	150		def load_data_shanghaitech_keepfull_and_crop(img_path, train=True):
	151		"""
	152		loader might give full image, or crop
	153		:param img_path:
	154		:param train:
	155		:return:
	156		"""
	157		gt_path = img_path.replace('.jpg', '.h5').replace('images', 'ground-truth-h5')
	158		img = Image.open(img_path).convert('RGB')
	159		gt_file = h5py.File(gt_path, 'r')
	160		target = np.asarray(gt_file['density'])
	161
	162		if train:
	163
	164		if random.random() > 0.5: # 50% chance crop
	165		crop_size = (int(img.size[0] / 2), int(img.size[1] / 2))
	166		if random.randint(0, 9) <= -1:
	167
	168		dx = int(random.randint(0, 1) * img.size[0] * 1. / 2)
	169		dy = int(random.randint(0, 1) * img.size[1] * 1. / 2)
	170		else:
	171		dx = int(random.random() * img.size[0] * 1. / 2)
	172		dy = int(random.random() * img.size[1] * 1. / 2)
	173
	174		img = img.crop((dx, dy, crop_size[0] + dx, crop_size[1] + dy))
	175		target = target[dy:crop_size[1] + dy, dx:crop_size[0] + dx]
	176
	177		if random.random() > 0.8: # 20 % chance flip
	178		target = np.fliplr(target)
	179		img = img.transpose(Image.FLIP_LEFT_RIGHT)
	180
	181		target1 = cv2.resize(target, (int(target.shape[1] / 8), int(target.shape[0] / 8)),
	182		interpolation=cv2.INTER_CUBIC) * 64
	183
	184		target1 = np.expand_dims(target1, axis=0) # make dim (batch size, channel size, x, y) to make model output
	185		# np.expand_dims(target1, axis=0) # again
	186		return img, target1
	187
	188
	189
150	190	def load_data_ucf_cc50(img_path, train=True):	def load_data_ucf_cc50(img_path, train=True):
151	191	gt_path = img_path.replace('.jpg', '.h5')	gt_path = img_path.replace('.jpg', '.h5')
152	192	img = Image.open(img_path).convert('RGB')	img = Image.open(img_path).convert('RGB')

...	...	class ListDataset(Dataset):
346	386	# load data fn	# load data fn
347	387	if dataset_name == "shanghaitech":	if dataset_name == "shanghaitech":
348	388	self.load_data_fn = load_data_shanghaitech	self.load_data_fn = load_data_shanghaitech
349		if dataset_name == "shanghaitech_same_size_density_map":
	389		elif dataset_name == "shanghaitech_same_size_density_map":
350	390	self.load_data_fn = load_data_shanghaitech_same_size_density_map	self.load_data_fn = load_data_shanghaitech_same_size_density_map
351		if dataset_name == "shanghaitech_keepfull":
	391		elif dataset_name == "shanghaitech_keepfull":
352	392	self.load_data_fn = load_data_shanghaitech_keepfull	self.load_data_fn = load_data_shanghaitech_keepfull
	393		elif dataset_name == "shanghaitech_keepfull_and_crop":
	394		self.load_data_fn = load_data_shanghaitech_keepfull_and_crop
353	395	elif dataset_name == "ucf_cc_50":	elif dataset_name == "ucf_cc_50":
354	396	self.load_data_fn = load_data_ucf_cc50	self.load_data_fn = load_data_ucf_cc50
355	397	elif dataset_name == "ucf_cc_50_pacnn":	elif dataset_name == "ucf_cc_50_pacnn":

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