<jupyter_start><jupyter_text><jupyter_code>!git clone https://github.com/Syilun/SSR-Net_megaage-asian.git
!git clone https://github.com/shamangary/SSR-Net.git
!pip install mtcnn
!pip install keras_applications
!pip uninstall TensorFlow
!pip uninstall Keras

!pip install TensorFlow==1.10.1
!pip install Keras==2.2.4

!pip install Pygame
# import scipy.io
# import numpy as np
# import pandas as pd
# from datetime import datetime, timedelta

# #import tensorflow as tf
# #from tensorflow import keras
# import keras
# from keras.preprocessing.image import load_img
# from keras.callbacks import ModelCheckpoint,EarlyStopping
# from keras.layers import Dense, Activation, Dropout, Flatten, Input, Convolution2D, ZeroPadding2D, MaxPooling2D, Activation
# from keras.layers import Conv2D, AveragePooling2D, BatchNormalization
# from keras.models import Model, Sequential

# from sklearn.model_selection import train_test_split
# from keras.utils import to_categorical
# from keras import metrics

# import matplotlib.pyplot as plt
# %matplotlib inline

# from keras.models import load_model
# import cv2
# from glob import glob
# import os
# from mtcnn import MTCNN
%cd /content/SSR-Net/demo
import os
os.environ["SDL_VIDEODRIVER"] = "dummy"
# !KERAS_BACKEND=tensorflow CUDA_VISIBLE_DEVICES='' python TYY_demo_mtcnn.py TGOP.mp4
!pip install opencv-contrib-python
!KERAS_BACKEND=tensorflow CUDA_VISIBLE_DEVICES='' python TYY_demo_ssrnet_lbp_webcam.py
# !python SSRNET_model.py
# from SSR-Net.demo.SSRNET_model import SSR_Net
# from keras_vggface.utils import preprocess_input
# feature_extractor = VGGFace(model='resnet50', include_top=False, 
#             input_shape=(224, 224, 3), pooling='avg')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08811594202898551, 'fraction_numerical': 0.013333333333333334, 'mean_word_length': 6.016260162601626, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 2, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '211934', 'license': 'Apache-2.0', 'n_tokens_mistral': 626, 'n_tokens_neox': 593, 'n_words': 152, 'path': 'SSR_Net_v2.ipynb', 'repo_name': 'Syilun/SSR-Net', 'size': '1725'}