Pie31415 commited on
Commit
54e0381
β€’
1 Parent(s): 59d0e29

fixed app issue

Browse files
Files changed (5) hide show
  1. app.py +111 -128
  2. examples/lincoln.jpg +0 -0
  3. examples/taras1.jpg +0 -0
  4. examples/taras2.jpg +0 -0
  5. requirements.txt +413 -15
app.py CHANGED
@@ -1,146 +1,130 @@
1
  import os, sys
2
- import importlib
3
  import argparse
4
 
5
  import numpy as np
6
  import torch
7
  import matplotlib.pyplot as plt
8
-
9
  from PIL import Image
10
 
11
- sys.path.append("./rome/")
12
-
13
  from rome.src.utils import args as args_utils
14
  from rome.src.utils.processing import process_black_shape, tensor2image
15
 
 
 
 
16
  # loading models ---- create model repo
17
- from huggingface_hub import hf_hub_url
18
 
19
- default_modnet_path = hf_hub_url('Pie31415/rome','modnet_photographic_portrait_matting.ckpt')
20
- default_model_path = hf_hub_url('Pie31415/rome','models/rome.pth')
21
 
22
  # parser configurations
23
- parser = argparse.ArgumentParser(conflict_handler='resolve')
24
- parser.add_argument('--save_dir', default='.', type=str)
25
- parser.add_argument('--save_render', default='True', type=args_utils.str2bool, choices=[True, False])
26
- parser.add_argument('--model_checkpoint', default=default_model_path, type=str)
27
- parser.add_argument('--modnet_path', default=default_modnet_path, type=str)
28
- parser.add_argument('--random_seed', default=0, type=int)
29
- parser.add_argument('--debug', action='store_true')
30
- parser.add_argument('--verbose', default='False', type=args_utils.str2bool, choices=[True, False])
31
- parser.add_argument('--model_image_size', default=256, type=int)
32
- parser.add_argument('--align_source', default='True', type=args_utils.str2bool, choices=[True, False])
33
- parser.add_argument('--align_target', default='False', type=args_utils.str2bool, choices=[True, False])
34
- parser.add_argument('--align_scale', default=1.25, type=float)
35
-
36
- parser.add_argument('--use_mesh_deformations', default='False', type=args_utils.str2bool, choices=[True, False])
37
- parser.add_argument('--subdivide_mesh', default='False', type=args_utils.str2bool, choices=[True, False])
38
- parser.add_argument('--renderer_sigma', default=1e-8, type=float)
39
- parser.add_argument('--renderer_zfar', default=100.0, type=float)
40
- parser.add_argument('--renderer_type', default='soft_mesh')
41
- parser.add_argument('--renderer_texture_type', default='texture_uv')
42
- parser.add_argument('--renderer_normalized_alphas', default='False', type=args_utils.str2bool,
43
- choices=[True, False])
44
-
45
- parser.add_argument('--deca_path', default='')
46
- parser.add_argument('--rome_data_dir', default='')
47
-
48
-
49
- parser.add_argument('--autoenc_cat_alphas', default='False', type=args_utils.str2bool, choices=[True, False])
50
- parser.add_argument('--autoenc_align_inputs', default='False', type=args_utils.str2bool, choices=[True, False])
51
- parser.add_argument('--autoenc_use_warp', default='False', type=args_utils.str2bool, choices=[True, False])
52
- parser.add_argument('--autoenc_num_channels', default=64, type=int)
53
- parser.add_argument('--autoenc_max_channels', default=512, type=int)
54
- parser.add_argument('--autoenc_num_groups', default=4, type=int)
55
- parser.add_argument('--autoenc_num_bottleneck_groups', default=0, type=int)
56
- parser.add_argument('--autoenc_num_blocks', default=2, type=int)
57
- parser.add_argument('--autoenc_num_layers', default=4, type=int)
58
- parser.add_argument('--autoenc_block_type', default='bottleneck')
59
-
60
- parser.add_argument('--neural_texture_channels', default=8, type=int)
61
- parser.add_argument('--num_harmonic_encoding_funcs', default=6, type=int)
62
-
63
- parser.add_argument('--unet_num_channels', default=64, type=int)
64
- parser.add_argument('--unet_max_channels', default=512, type=int)
65
- parser.add_argument('--unet_num_groups', default=4, type=int)
66
- parser.add_argument('--unet_num_blocks', default=1, type=int)
67
- parser.add_argument('--unet_num_layers', default=2, type=int)
68
- parser.add_argument('--unet_block_type', default='conv')
69
- parser.add_argument('--unet_skip_connection_type', default='cat')
70
- parser.add_argument('--unet_use_normals_cond', default=True, action='store_true')
71
- parser.add_argument('--unet_use_vertex_cond', action='store_true')
72
- parser.add_argument('--unet_use_uvs_cond', action='store_true')
73
- parser.add_argument('--unet_pred_mask', action='store_true')
74
- parser.add_argument('--use_separate_seg_unet', default='True', type=args_utils.str2bool, choices=[True, False])
75
-
76
- parser.add_argument('--norm_layer_type', default='gn', type=str, choices=['bn', 'sync_bn', 'in', 'gn'])
77
- parser.add_argument('--activation_type', default='relu', type=str, choices=['relu', 'lrelu'])
78
- parser.add_argument('--conv_layer_type', default='ws_conv', type=str, choices=['conv', 'ws_conv'])
79
-
80
- parser.add_argument('--deform_norm_layer_type', default='gn', type=str, choices=['bn', 'sync_bn', 'in', 'gn'])
81
- parser.add_argument('--deform_activation_type', default='relu', type=str, choices=['relu', 'lrelu'])
82
- parser.add_argument('--deform_conv_layer_type', default='ws_conv', type=str, choices=['conv', 'ws_conv'])
83
- parser.add_argument('--unet_seg_weight', default=0.0, type=float)
84
- parser.add_argument('--unet_seg_type', default='bce_with_logits', type=str, choices=['bce_with_logits', 'dice'])
85
- parser.add_argument('--deform_face_tightness', default=0.0, type=float)
86
-
87
- parser.add_argument('--use_whole_segmentation', action='store_true')
88
- parser.add_argument('--mask_hair_for_neck', action='store_true')
89
- parser.add_argument('--use_hair_from_avatar', action='store_true')
90
-
91
- # Basis deformations
92
- parser.add_argument('--use_scalp_deforms', default='True', type=args_utils.str2bool,
93
- choices=[True, False], help='')
94
- parser.add_argument('--use_neck_deforms', default='True', type=args_utils.str2bool,
95
- choices=[True, False], help='')
96
- parser.add_argument('--use_basis_deformer', default='False', type=args_utils.str2bool,
97
- choices=[True, False], help='')
98
- parser.add_argument('--use_unet_deformer', default='True', type=args_utils.str2bool,
99
- choices=[True, False], help='')
100
-
101
- parser.add_argument('--pretrained_encoder_basis_path', default='')
102
- parser.add_argument('--pretrained_vertex_basis_path', default='')
103
- parser.add_argument('--num_basis', default=50, type=int)
104
- parser.add_argument('--basis_init', default='pca', type=str, choices=['random', 'pca'])
105
- parser.add_argument('--num_vertex', default=5023, type=int)
106
- parser.add_argument('--train_basis', default=True, type=args_utils.str2bool, choices=[True, False])
107
- parser.add_argument('--path_to_deca', default='DECA')
108
-
109
- parser.add_argument('--path_to_linear_hair_model',
110
- default='data/linear_hair.pth')
111
- parser.add_argument('--path_to_mobile_model',
112
- default='data/disp_model.pth')
113
- parser.add_argument('--n_scalp', default=60, type=int)
114
-
115
- parser.add_argument('--use_distill', default=False, type=args_utils.str2bool, choices=[True, False])
116
- parser.add_argument('--use_mobile_version', default=False, type=args_utils.str2bool, choices=[True, False])
117
-
118
- parser.add_argument('--deformer_path', default='data/rome.pth')
119
-
120
- parser.add_argument('--output_unet_deformer_feats', default=32, type=int,
121
- help='output features in the UNet')
122
-
123
- parser.add_argument('--use_deca_details', default=False, type=args_utils.str2bool, choices=[True, False])
124
- parser.add_argument('--use_flametex', default=False, type=args_utils.str2bool, choices=[True, False])
125
-
126
- parser.add_argument('--upsample_type', default='nearest', type=str,
127
- choices=['nearest', 'bilinear', 'bicubic'])
128
-
129
- parser.add_argument('--num_frequencies', default=6, type=int, help='frequency for harmonic encoding')
130
- parser.add_argument('--deform_face_scale_coef', default=0.0, type=float)
131
- parser.add_argument('--device', default='cpu', type=str)
132
- # args, _ = parser.parse_known_args()
133
-
134
- # parser = importlib.import_module(f'src.rome').ROME.add_argparse_args(parser)
135
- args = parser.parse_args()
136
- args.deca_path = 'DECA'
137
-
138
- device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
139
-
140
- from infer import Infer
141
-
142
  infer = Infer(args)
143
- infer = infer.to(device)
144
 
145
  def predict(source_img, driver_img):
146
  out = infer.evaluate(source_img, driver_img, crop_center=False)
@@ -149,7 +133,6 @@ def predict(source_img, driver_img):
149
  out['render_masked'].cpu(), out['pred_target_shape_img'][0].cpu()], dim=2))
150
  return res[..., ::-1]
151
 
152
-
153
  import gradio as gr
154
 
155
  gr.Interface(
 
1
  import os, sys
2
+ import torch
3
  import argparse
4
 
5
  import numpy as np
6
  import torch
7
  import matplotlib.pyplot as plt
 
8
  from PIL import Image
9
 
 
 
10
  from rome.src.utils import args as args_utils
11
  from rome.src.utils.processing import process_black_shape, tensor2image
12
 
13
+ sys.path.append("./rome/")
14
+ sys.path.append('./DECA')
15
+
16
  # loading models ---- create model repo
17
+ from huggingface_hub import hf_hub_download
18
 
19
+ default_modnet_path = hf_hub_download('Pie31415/rome','modnet_photographic_portrait_matting.ckpt')
20
+ default_model_path = hf_hub_download('Pie31415/rome','rome.pth')
21
 
22
  # parser configurations
23
+ from easydict import EasyDict as edict
24
+
25
+ args = edict({
26
+ "save_dir": ".",
27
+ "save_render": True,
28
+ "model_checkpoint": default_model_path,
29
+ "modnet_path": default_modnet_path,
30
+ "random_seed": 0,
31
+ "debug": False,
32
+ "verbose": False,
33
+ "model_image_size": 256,
34
+ "align_source": True,
35
+ "align_target": False,
36
+ "align_scale": 1.25,
37
+ "use_mesh_deformations": False,
38
+ "subdivide_mesh": False,
39
+ "renderer_sigma": 1e-08,
40
+ "renderer_zfar": 100.0,
41
+ "renderer_type": "soft_mesh",
42
+ "renderer_texture_type": "texture_uv",
43
+ "renderer_normalized_alphas": False,
44
+ "deca_path": "DECA",
45
+ "rome_data_dir": "rome/data",
46
+ "autoenc_cat_alphas": False,
47
+ "autoenc_align_inputs": False,
48
+ "autoenc_use_warp": False,
49
+ "autoenc_num_channels": 64,
50
+ "autoenc_max_channels": 512,
51
+ "autoenc_num_groups": 4,
52
+ "autoenc_num_bottleneck_groups": 0,
53
+ "autoenc_num_blocks": 2,
54
+ "autoenc_num_layers": 4,
55
+ "autoenc_block_type": "bottleneck",
56
+ "neural_texture_channels": 8,
57
+ "num_harmonic_encoding_funcs": 6,
58
+ "unet_num_channels": 64,
59
+ "unet_max_channels": 512,
60
+ "unet_num_groups": 4,
61
+ "unet_num_blocks": 1,
62
+ "unet_num_layers": 2,
63
+ "unet_block_type": "conv",
64
+ "unet_skip_connection_type": "cat",
65
+ "unet_use_normals_cond": True,
66
+ "unet_use_vertex_cond": False,
67
+ "unet_use_uvs_cond": False,
68
+ "unet_pred_mask": False,
69
+ "use_separate_seg_unet": True,
70
+ "norm_layer_type": "gn",
71
+ "activation_type": "relu",
72
+ "conv_layer_type": "ws_conv",
73
+ "deform_norm_layer_type": "gn",
74
+ "deform_activation_type": "relu",
75
+ "deform_conv_layer_type": "ws_conv",
76
+ "unet_seg_weight": 0.0,
77
+ "unet_seg_type": "bce_with_logits",
78
+ "deform_face_tightness": 0.0001,
79
+ "use_whole_segmentation": False,
80
+ "mask_hair_for_neck": False,
81
+ "use_hair_from_avatar": False,
82
+ "use_scalp_deforms": True,
83
+ "use_neck_deforms": True,
84
+ "use_basis_deformer": False,
85
+ "use_unet_deformer": True,
86
+ "pretrained_encoder_basis_path": "",
87
+ "pretrained_vertex_basis_path": "",
88
+ "num_basis": 50,
89
+ "basis_init": "pca",
90
+ "num_vertex": 5023,
91
+ "train_basis": True,
92
+ "path_to_deca": "DECA",
93
+ "path_to_linear_hair_model": "data/linear_hair.pth", # N/A
94
+ "path_to_mobile_model": "data/disp_model.pth", # N/A
95
+ "n_scalp": 60,
96
+ "use_distill": False,
97
+ "use_mobile_version": False,
98
+ "deformer_path": "data/rome.pth",
99
+ "output_unet_deformer_feats": 32,
100
+ "use_deca_details": False,
101
+ "use_flametex": False,
102
+ "upsample_type": "nearest",
103
+ "num_frequencies": 6,
104
+ "deform_face_scale_coef": 0.0,
105
+ "device": "cpu"
106
+ })
107
+
108
+ # download FLAME and DECA pretrained
109
+ generic_model_path = hf_hub_download('Pie31415/rome','generic_model.pkl')
110
+ deca_model_path = hf_hub_download('Pie31415/rome','deca_model.tar')
111
+
112
+ import pickle
113
+
114
+ with open(generic_model_path, 'rb') as f:
115
+ ss = pickle.load(f, encoding='latin1')
116
+
117
+ with open('./DECA/data/generic_model.pkl', 'wb') as out:
118
+ pickle.dump(ss, out)
119
+
120
+ with open(deca_model_path, "rb") as input:
121
+ with open('./DECA/data/deca_model.tar', "wb") as out:
122
+ for line in input:
123
+ out.write(line)
124
+
125
+ # load ROME inference model
126
+ from rome.infer import Infer
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
127
  infer = Infer(args)
 
128
 
129
  def predict(source_img, driver_img):
130
  out = infer.evaluate(source_img, driver_img, crop_center=False)
 
133
  out['render_masked'].cpu(), out['pred_target_shape_img'][0].cpu()], dim=2))
134
  return res[..., ::-1]
135
 
 
136
  import gradio as gr
137
 
138
  gr.Interface(
examples/lincoln.jpg ADDED
examples/taras1.jpg ADDED
examples/taras2.jpg ADDED
requirements.txt CHANGED
@@ -1,16 +1,414 @@
1
- numpy>=1.18.5
2
- scipy>=1.4.1
3
- chumpy>=0.69
4
- scikit-image>=0.15
5
- opencv-python>=4.1.1
6
- scikit-image>=0.15 #skimage
7
- PyYAML==5.1.1
8
- torch==1.6.0
9
- torchvision==0.7.0
10
- face-alignment
11
- yacs==0.1.8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
12
  kornia==0.4.0
13
- ninja
14
- fvcore
15
- argparse
16
- pytorch3d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ absl-py==1.3.0
2
+ aeppl==0.0.33
3
+ aesara==2.7.9
4
+ aiohttp==3.8.3
5
+ aiosignal==1.3.1
6
+ alabaster==0.7.12
7
+ albumentations==1.2.1
8
+ altair==4.2.0
9
+ appdirs==1.4.4
10
+ arviz==0.12.1
11
+ astor==0.8.1
12
+ astropy==4.3.1
13
+ astunparse==1.6.3
14
+ async-timeout==4.0.2
15
+ atari-py==0.2.9
16
+ atomicwrites==1.4.1
17
+ attrs==22.1.0
18
+ audioread==3.0.0
19
+ autograd==1.5
20
+ Babel==2.11.0
21
+ backcall==0.2.0
22
+ beautifulsoup4==4.6.3
23
+ bleach==5.0.1
24
+ blis==0.7.9
25
+ bokeh==2.3.3
26
+ branca==0.6.0
27
+ bs4==0.0.1
28
+ CacheControl==0.12.11
29
+ cachetools==5.2.0
30
+ catalogue==2.0.8
31
+ certifi==2022.12.7
32
+ cffi==1.15.1
33
+ cftime==1.6.2
34
+ chardet==3.0.4
35
+ charset-normalizer==2.1.1
36
+ chumpy==0.70
37
+ click==7.1.2
38
+ clikit==0.6.2
39
+ cloudpickle==1.5.0
40
+ cmake==3.22.6
41
+ cmdstanpy==1.0.8
42
+ colorcet==3.0.1
43
+ colorlover==0.3.0
44
+ community==1.0.0b1
45
+ confection==0.0.3
46
+ cons==0.4.5
47
+ contextlib2==0.5.5
48
+ convertdate==2.4.0
49
+ crashtest==0.3.1
50
+ crcmod==1.7
51
+ cufflinks==0.17.3
52
+ cupy-cuda11x==11.0.0
53
+ cvxopt==1.3.0
54
+ cvxpy==1.2.2
55
+ cycler==0.11.0
56
+ cymem==2.0.7
57
+ Cython==0.29.32
58
+ daft==0.0.4
59
+ dask==2022.2.1
60
+ datascience==0.17.5
61
+ db-dtypes==1.0.5
62
+ debugpy==1.0.0
63
+ decorator==4.4.2
64
+ defusedxml==0.7.1
65
+ descartes==1.1.0
66
+ dill==0.3.6
67
+ distributed==2022.2.1
68
+ dlib==19.24.0
69
+ dm-tree==0.1.7
70
+ dnspython==2.2.1
71
+ docutils==0.17.1
72
+ dopamine-rl==1.0.5
73
+ earthengine-api==0.1.335
74
+ easydict==1.10
75
+ ecos==2.0.10
76
+ editdistance==0.5.3
77
+ en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.4.1/en_core_web_sm-3.4.1-py3-none-any.whl
78
+ entrypoints==0.4
79
+ ephem==4.1.3
80
+ et-xmlfile==1.1.0
81
+ etils==0.9.0
82
+ etuples==0.3.8
83
+ fa2==0.3.5
84
+ face-alignment==1.3.5
85
+ fastai==2.7.10
86
+ fastcore==1.5.27
87
+ fastdownload==0.0.7
88
+ fastdtw==0.3.4
89
+ fastjsonschema==2.16.2
90
+ fastprogress==1.0.3
91
+ fastrlock==0.8.1
92
+ feather-format==0.4.1
93
+ filelock==3.8.2
94
+ firebase-admin==5.3.0
95
+ fix-yahoo-finance==0.0.22
96
+ Flask==1.1.4
97
+ flatbuffers==1.12
98
+ folium==0.12.1.post1
99
+ frozenlist==1.3.3
100
+ fsspec==2022.11.0
101
+ future==0.16.0
102
+ fvcore==0.1.5.post20221221
103
+ gast==0.4.0
104
+ GDAL==2.2.2
105
+ gdown==4.4.0
106
+ gensim==3.6.0
107
+ geographiclib==1.52
108
+ geopy==1.17.0
109
+ gin-config==0.5.0
110
+ glob2==0.7
111
+ google==2.0.3
112
+ google-api-core==2.8.2
113
+ google-api-python-client==1.12.11
114
+ google-auth==2.15.0
115
+ google-auth-httplib2==0.0.4
116
+ google-auth-oauthlib==0.4.6
117
+ google-cloud-bigquery==3.3.6
118
+ google-cloud-bigquery-storage==2.16.2
119
+ google-cloud-core==2.3.2
120
+ google-cloud-datastore==2.9.0
121
+ google-cloud-firestore==2.7.2
122
+ google-cloud-language==2.6.1
123
+ google-cloud-storage==2.5.0
124
+ google-cloud-translate==3.8.4
125
+ google-colab @ file:///colabtools/dist/google-colab-1.0.0.tar.gz
126
+ google-crc32c==1.5.0
127
+ google-pasta==0.2.0
128
+ google-resumable-media==2.4.0
129
+ googleapis-common-protos==1.57.0
130
+ googledrivedownloader==0.4
131
+ graphviz==0.10.1
132
+ greenlet==2.0.1
133
+ grpcio==1.51.1
134
+ grpcio-status==1.48.2
135
+ gspread==3.4.2
136
+ gspread-dataframe==3.0.8
137
+ gym==0.25.2
138
+ gym-notices==0.0.8
139
+ h5py==3.1.0
140
+ HeapDict==1.0.1
141
+ hijri-converter==2.2.4
142
+ holidays==0.17.2
143
+ holoviews==1.14.9
144
+ html5lib==1.0.1
145
+ httpimport==0.5.18
146
+ httplib2==0.17.4
147
+ httpstan==4.6.1
148
+ huggingface-hub==0.11.1
149
+ humanize==0.5.1
150
+ hyperopt==0.1.2
151
+ idna==2.10
152
+ imageio==2.9.0
153
+ imagesize==1.4.1
154
+ imbalanced-learn==0.8.1
155
+ imblearn==0.0
156
+ imgaug==0.4.0
157
+ importlib-metadata==5.1.0
158
+ importlib-resources==5.10.1
159
+ imutils==0.5.4
160
+ inflect==2.1.0
161
+ intel-openmp==2022.2.1
162
+ intervaltree==2.1.0
163
+ iopath==0.1.10
164
+ ipykernel==5.3.4
165
+ ipython==7.9.0
166
+ ipython-genutils==0.2.0
167
+ ipython-sql==0.3.9
168
+ ipywidgets==7.7.1
169
+ itsdangerous==1.1.0
170
+ jax==0.3.25
171
+ jaxlib @ https://storage.googleapis.com/jax-releases/cuda11/jaxlib-0.3.25+cuda11.cudnn805-cp38-cp38-manylinux2014_x86_64.whl
172
+ jieba==0.42.1
173
+ Jinja2==2.11.3
174
+ joblib==1.2.0
175
+ jpeg4py==0.1.4
176
+ jsonschema==4.3.3
177
+ jupyter-client==6.1.12
178
+ jupyter-console==6.1.0
179
+ jupyter-core==5.1.0
180
+ jupyterlab-widgets==3.0.4
181
+ kaggle==1.5.12
182
+ kapre==0.3.7
183
+ keras==2.9.0
184
+ Keras-Preprocessing==1.1.2
185
+ keras-vis==0.4.1
186
+ kiwisolver==1.4.4
187
+ korean-lunar-calendar==0.3.1
188
  kornia==0.4.0
189
+ langcodes==3.3.0
190
+ libclang==14.0.6
191
+ librosa==0.8.1
192
+ lightgbm==2.2.3
193
+ llvmlite==0.39.1
194
+ lmdb==0.99
195
+ locket==1.0.0
196
+ logical-unification==0.4.5
197
+ LunarCalendar==0.0.9
198
+ lxml==4.9.2
199
+ Markdown==3.4.1
200
+ MarkupSafe==2.0.1
201
+ marshmallow==3.19.0
202
+ matplotlib==3.2.2
203
+ matplotlib-venn==0.11.7
204
+ miniKanren==1.0.3
205
+ missingno==0.5.1
206
+ mistune==0.8.4
207
+ mizani==0.7.3
208
+ mkl==2019.0
209
+ mlxtend==0.14.0
210
+ more-itertools==9.0.0
211
+ moviepy==0.2.3.5
212
+ mpmath==1.2.1
213
+ msgpack==1.0.4
214
+ multidict==6.0.3
215
+ multipledispatch==0.6.0
216
+ multitasking==0.0.11
217
+ murmurhash==1.0.9
218
+ music21==5.5.0
219
+ natsort==5.5.0
220
+ nbconvert==5.6.1
221
+ nbformat==5.7.0
222
+ netCDF4==1.6.2
223
+ networkx==2.8.8
224
+ nibabel==3.0.2
225
+ nltk==3.7
226
+ notebook==5.7.16
227
+ numba==0.56.4
228
+ numexpr==2.8.4
229
+ numpy==1.21.6
230
+ oauth2client==4.1.3
231
+ oauthlib==3.2.2
232
+ okgrade==0.4.3
233
+ opencv-contrib-python==4.6.0.66
234
+ opencv-python==4.6.0.66
235
+ opencv-python-headless==4.6.0.66
236
+ openpyxl==3.0.10
237
+ opt-einsum==3.3.0
238
+ osqp==0.6.2.post0
239
+ packaging==21.3
240
+ palettable==3.3.0
241
+ pandas==1.3.5
242
+ pandas-datareader==0.9.0
243
+ pandas-gbq==0.17.9
244
+ pandas-profiling==1.4.1
245
+ pandocfilters==1.5.0
246
+ panel==0.12.1
247
+ param==1.12.3
248
+ parso==0.8.3
249
+ partd==1.3.0
250
+ pastel==0.2.1
251
+ pathlib==1.0.1
252
+ pathy==0.10.1
253
+ patsy==0.5.3
254
+ pep517==0.13.0
255
+ pexpect==4.8.0
256
+ pickleshare==0.7.5
257
+ Pillow==7.1.2
258
+ pip-tools==6.2.0
259
+ platformdirs==2.6.0
260
+ plotly==5.5.0
261
+ plotnine==0.8.0
262
+ pluggy==0.7.1
263
+ pooch==1.6.0
264
+ portalocker==2.6.0
265
+ portpicker==1.3.9
266
+ prefetch-generator==1.0.3
267
+ preshed==3.0.8
268
+ prettytable==3.5.0
269
+ progressbar2==3.38.0
270
+ prometheus-client==0.15.0
271
+ promise==2.3
272
+ prompt-toolkit==2.0.10
273
+ prophet==1.1.1
274
+ proto-plus==1.22.1
275
+ protobuf==3.19.6
276
+ psutil==5.4.8
277
+ psycopg2==2.9.5
278
+ ptyprocess==0.7.0
279
+ py==1.11.0
280
+ pyarrow==9.0.0
281
+ pyasn1==0.4.8
282
+ pyasn1-modules==0.2.8
283
+ pycocotools==2.0.6
284
+ pycparser==2.21
285
+ pyct==0.4.8
286
+ pydantic==1.10.2
287
+ pydata-google-auth==1.4.0
288
+ pydot==1.3.0
289
+ pydot-ng==2.0.0
290
+ pydotplus==2.0.2
291
+ PyDrive==1.3.1
292
+ pyemd==0.5.1
293
+ pyerfa==2.0.0.1
294
+ Pygments==2.6.1
295
+ pygobject==3.26.1
296
+ pylev==1.4.0
297
+ pymc==4.1.4
298
+ PyMeeus==0.5.12
299
+ pymongo==4.3.3
300
+ pymystem3==0.2.0
301
+ PyOpenGL==3.1.6
302
+ pyparsing==3.0.9
303
+ pyrsistent==0.19.2
304
+ pysimdjson==3.2.0
305
+ pysndfile==1.3.8
306
+ PySocks==1.7.1
307
+ pystan==3.3.0
308
+ pytest==3.6.4
309
+ python-apt==0.0.0
310
+ python-dateutil==2.8.2
311
+ python-louvain==0.16
312
+ python-slugify==7.0.0
313
+ python-utils==3.4.5
314
+ pytorch3d==0.3.0
315
+ pytz==2022.6
316
+ pyviz-comms==2.2.1
317
+ PyWavelets==1.4.1
318
+ PyYAML==6.0
319
+ pyzmq==23.2.1
320
+ qdldl==0.1.5.post2
321
+ qudida==0.0.4
322
+ regex==2022.6.2
323
+ requests==2.23.0
324
+ requests-oauthlib==1.3.1
325
+ resampy==0.4.2
326
+ rpy2==3.5.5
327
+ rsa==4.9
328
+ scikit-image==0.18.3
329
+ scikit-learn==1.0.2
330
+ scipy==1.7.3
331
+ screen-resolution-extra==0.0.0
332
+ scs==3.2.2
333
+ seaborn==0.11.2
334
+ Send2Trash==1.8.0
335
+ setuptools-git==1.2
336
+ shapely==2.0.0
337
+ six==1.15.0
338
+ sklearn-pandas==1.8.0
339
+ smart-open==6.3.0
340
+ snowballstemmer==2.2.0
341
+ sortedcontainers==2.4.0
342
+ soundfile==0.11.0
343
+ spacy==3.4.4
344
+ spacy-legacy==3.0.10
345
+ spacy-loggers==1.0.4
346
+ Sphinx==1.8.6
347
+ sphinxcontrib-serializinghtml==1.1.5
348
+ sphinxcontrib-websupport==1.2.4
349
+ SQLAlchemy==1.4.45
350
+ sqlparse==0.4.3
351
+ srsly==2.4.5
352
+ statsmodels==0.12.2
353
+ sympy==1.7.1
354
+ tables==3.7.0
355
+ tabulate==0.8.10
356
+ tblib==1.7.0
357
+ tenacity==8.1.0
358
+ tensorboard==2.9.1
359
+ tensorboard-data-server==0.6.1
360
+ tensorboard-plugin-wit==1.8.1
361
+ tensorflow==2.9.2
362
+ tensorflow-datasets==4.6.0
363
+ tensorflow-estimator==2.9.0
364
+ tensorflow-gcs-config==2.9.1
365
+ tensorflow-hub==0.12.0
366
+ tensorflow-io-gcs-filesystem==0.28.0
367
+ tensorflow-metadata==1.12.0
368
+ tensorflow-probability==0.17.0
369
+ termcolor==2.1.1
370
+ terminado==0.13.3
371
+ testpath==0.6.0
372
+ text-unidecode==1.3
373
+ textblob==0.15.3
374
+ thinc==8.1.5
375
+ threadpoolctl==3.1.0
376
+ tifffile==2022.10.10
377
+ toml==0.10.2
378
+ tomli==2.0.1
379
+ toolz==0.12.0
380
+ torch==1.6.0+cu101
381
+ torchaudio @ https://download.pytorch.org/whl/cu116/torchaudio-0.13.0%2Bcu116-cp38-cp38-linux_x86_64.whl
382
+ torchsummary==1.5.1
383
+ torchtext==0.14.0
384
+ torchvision==0.7.0+cu101
385
+ tornado==6.0.4
386
+ tqdm==4.64.1
387
+ traitlets==5.7.1
388
+ tweepy==3.10.0
389
+ typeguard==2.7.1
390
+ typer==0.7.0
391
+ typing-extensions==4.4.0
392
+ tzlocal==1.5.1
393
+ uritemplate==3.0.1
394
+ urllib3==1.24.3
395
+ vega-datasets==0.9.0
396
+ wasabi==0.10.1
397
+ wcwidth==0.2.5
398
+ webargs==8.2.0
399
+ webencodings==0.5.1
400
+ Werkzeug==1.0.1
401
+ widgetsnbextension==3.6.1
402
+ wordcloud==1.8.2.2
403
+ wrapt==1.14.1
404
+ xarray==2022.12.0
405
+ xarray-einstats==0.4.0
406
+ xgboost==0.90
407
+ xkit==0.0.0
408
+ xlrd==1.2.0
409
+ xlwt==1.3.0
410
+ yacs==0.1.8
411
+ yarl==1.8.2
412
+ yellowbrick==1.5
413
+ zict==2.2.0
414
+ zipp==3.11.0