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| import tensorflow as tf | |
| from pathlib import Path | |
| import pandas as pd | |
| from tqdm import tqdm | |
| from collections import defaultdict | |
| # Get all event* runs from logging_dir subdirectories | |
| logging_dir = Path('.', 'logs') | |
| event_paths = logging_dir.glob('**/event*') |
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| cmake \ | |
| -D CMAKE_BUILD_TYPE=RELEASE \ | |
| -D CMAKE_INSTALL_PREFIX=/path/to/anaconda3/ \ | |
| -D BUILD_NEW_PYTHON_SUPPORT=ON \ | |
| -D BUILD_OPENCV_PYTHON3=OFF \ | |
| -D BUILD_OPENCV_PYTHON2=OFF \ | |
| -D INSTALL_C_EXAMPLES=OFF \ | |
| -D INSTALL_PYTHON_EXAMPLES=OFF \ | |
| -D BUILD_EXAMPLES=OFF \ | |
| -D BUILD_JPEG=ON \ |
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| from torch.autograd import Variable | |
| import torch.nn as nn | |
| import torch | |
| # LSTM | |
| hidden_size = 20 | |
| num_layers = 2 | |
| num_directions = 1 | |
| # Input |
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| def dice(im1, im2, empty_score=1.0): | |
| """ | |
| Computes the Dice coefficient, a measure of set similarity. | |
| Parameters | |
| ---------- | |
| im1 : array-like, bool | |
| Any array of arbitrary size. If not boolean, will be converted. | |
| im2 : array-like, bool | |
| Any other array of identical size. If not boolean, will be converted. | |
| Returns |
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| // Convert a float RGB to int RGB. Note: does not check for floats outside range (0..1) | |
| public static int rgbFloatToInt(float r, float g, float b) { | |
| return ((int) (0xff * b)) | (((int) (0xff * g)) << 8 ) | (((int) (0xff * r)) << 16 ) ; | |
| } |
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| import java.util.HashMap; | |
| import java.util.Map; | |
| import java.util.Set; | |
| import java.util.function.Consumer; | |
| /** | |
| * Created by Bruno on 01/03/2015. | |
| * | |
| * Table with type R for rows, C for columns and V for values | |
| * |