Spaces:
Runtime error
Runtime error
fixed app issue
Browse files- app.py +111 -128
- examples/lincoln.jpg +0 -0
- examples/taras1.jpg +0 -0
- examples/taras2.jpg +0 -0
- requirements.txt +413 -15
app.py
CHANGED
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import os, sys
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import
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import argparse
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import numpy as np
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import torch
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import matplotlib.pyplot as plt
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from PIL import Image
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sys.path.append("./rome/")
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from rome.src.utils import args as args_utils
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from rome.src.utils.processing import process_black_shape, tensor2image
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# loading models ---- create model repo
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from huggingface_hub import
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default_modnet_path =
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default_model_path =
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# parser configurations
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choices=['nearest', 'bilinear', 'bicubic'])
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parser.add_argument('--num_frequencies', default=6, type=int, help='frequency for harmonic encoding')
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parser.add_argument('--deform_face_scale_coef', default=0.0, type=float)
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parser.add_argument('--device', default='cpu', type=str)
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# args, _ = parser.parse_known_args()
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# parser = importlib.import_module(f'src.rome').ROME.add_argparse_args(parser)
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args = parser.parse_args()
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args.deca_path = 'DECA'
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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from infer import Infer
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infer = Infer(args)
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infer = infer.to(device)
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def predict(source_img, driver_img):
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out = infer.evaluate(source_img, driver_img, crop_center=False)
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out['render_masked'].cpu(), out['pred_target_shape_img'][0].cpu()], dim=2))
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return res[..., ::-1]
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import gradio as gr
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gr.Interface(
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import os, sys
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import torch
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import argparse
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import numpy as np
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import torch
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import matplotlib.pyplot as plt
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from PIL import Image
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from rome.src.utils import args as args_utils
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from rome.src.utils.processing import process_black_shape, tensor2image
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sys.path.append("./rome/")
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sys.path.append('./DECA')
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# loading models ---- create model repo
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from huggingface_hub import hf_hub_download
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default_modnet_path = hf_hub_download('Pie31415/rome','modnet_photographic_portrait_matting.ckpt')
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default_model_path = hf_hub_download('Pie31415/rome','rome.pth')
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# parser configurations
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from easydict import EasyDict as edict
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args = edict({
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"save_dir": ".",
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"save_render": True,
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"model_checkpoint": default_model_path,
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"modnet_path": default_modnet_path,
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"random_seed": 0,
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"debug": False,
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"verbose": False,
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"model_image_size": 256,
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"align_source": True,
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"align_target": False,
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"align_scale": 1.25,
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"use_mesh_deformations": False,
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"subdivide_mesh": False,
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"renderer_sigma": 1e-08,
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"renderer_zfar": 100.0,
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"renderer_type": "soft_mesh",
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"renderer_texture_type": "texture_uv",
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"renderer_normalized_alphas": False,
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"deca_path": "DECA",
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"rome_data_dir": "rome/data",
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"autoenc_cat_alphas": False,
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"autoenc_align_inputs": False,
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"autoenc_use_warp": False,
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"autoenc_num_channels": 64,
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"autoenc_max_channels": 512,
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"autoenc_num_groups": 4,
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"autoenc_num_bottleneck_groups": 0,
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"autoenc_num_blocks": 2,
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"autoenc_num_layers": 4,
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"autoenc_block_type": "bottleneck",
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"neural_texture_channels": 8,
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"num_harmonic_encoding_funcs": 6,
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"unet_num_channels": 64,
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"unet_max_channels": 512,
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"unet_num_groups": 4,
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"unet_num_blocks": 1,
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"unet_num_layers": 2,
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"unet_block_type": "conv",
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"unet_skip_connection_type": "cat",
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"unet_use_normals_cond": True,
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"unet_use_vertex_cond": False,
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"unet_use_uvs_cond": False,
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"unet_pred_mask": False,
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"use_separate_seg_unet": True,
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"norm_layer_type": "gn",
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"activation_type": "relu",
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"conv_layer_type": "ws_conv",
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"deform_norm_layer_type": "gn",
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"deform_activation_type": "relu",
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"deform_conv_layer_type": "ws_conv",
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"unet_seg_weight": 0.0,
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"unet_seg_type": "bce_with_logits",
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"deform_face_tightness": 0.0001,
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"use_whole_segmentation": False,
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"mask_hair_for_neck": False,
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"use_hair_from_avatar": False,
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"use_scalp_deforms": True,
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"use_neck_deforms": True,
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"use_basis_deformer": False,
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"use_unet_deformer": True,
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"pretrained_encoder_basis_path": "",
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"pretrained_vertex_basis_path": "",
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"num_basis": 50,
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"basis_init": "pca",
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"num_vertex": 5023,
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"train_basis": True,
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"path_to_deca": "DECA",
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"path_to_linear_hair_model": "data/linear_hair.pth", # N/A
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"path_to_mobile_model": "data/disp_model.pth", # N/A
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"n_scalp": 60,
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"use_distill": False,
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"use_mobile_version": False,
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"deformer_path": "data/rome.pth",
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"output_unet_deformer_feats": 32,
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"use_deca_details": False,
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"use_flametex": False,
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"upsample_type": "nearest",
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"num_frequencies": 6,
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"deform_face_scale_coef": 0.0,
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"device": "cpu"
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})
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# download FLAME and DECA pretrained
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generic_model_path = hf_hub_download('Pie31415/rome','generic_model.pkl')
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deca_model_path = hf_hub_download('Pie31415/rome','deca_model.tar')
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import pickle
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with open(generic_model_path, 'rb') as f:
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ss = pickle.load(f, encoding='latin1')
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with open('./DECA/data/generic_model.pkl', 'wb') as out:
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pickle.dump(ss, out)
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with open(deca_model_path, "rb") as input:
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with open('./DECA/data/deca_model.tar', "wb") as out:
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for line in input:
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out.write(line)
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# load ROME inference model
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from rome.infer import Infer
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infer = Infer(args)
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def predict(source_img, driver_img):
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out = infer.evaluate(source_img, driver_img, crop_center=False)
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out['render_masked'].cpu(), out['pred_target_shape_img'][0].cpu()], dim=2))
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return res[..., ::-1]
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import gradio as gr
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gr.Interface(
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examples/lincoln.jpg
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examples/taras1.jpg
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examples/taras2.jpg
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requirements.txt
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kornia==0.4.0
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absl-py==1.3.0
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aeppl==0.0.33
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aesara==2.7.9
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aiohttp==3.8.3
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aiosignal==1.3.1
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alabaster==0.7.12
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albumentations==1.2.1
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altair==4.2.0
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appdirs==1.4.4
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arviz==0.12.1
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astor==0.8.1
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astropy==4.3.1
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astunparse==1.6.3
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async-timeout==4.0.2
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atari-py==0.2.9
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atomicwrites==1.4.1
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attrs==22.1.0
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audioread==3.0.0
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autograd==1.5
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Babel==2.11.0
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backcall==0.2.0
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beautifulsoup4==4.6.3
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bleach==5.0.1
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blis==0.7.9
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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
|