NOBATGELDI GELDIMAMMEDOV Nobatgeldi
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Nobatgeldi
/ downgrade_uasset.py
Created
July 20, 2022 20:06
Downgrade Unreal Engine 4.27 uasset to Unreal Engine 4.26.2
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| from pathlib import Path | |
| import binascii | |
| bytes_to_read = 2000 | |
| guids = { | |
| "Dev-Blueprints": "B0D832E41F894F0DACCF7EB736FD4AA2", | |
| "Dev-Build": "E1C64328A22C4D53A36C8E866417BD8C", | |
| "Dev-Core": "375EC13C06E448FBB50084F0262A717E", | |
| "Dev-Editor": "E4B068EDF49442E9A231DA0B2E46BB41", | |
| "Dev-Framework": "CFFC743F43B04480939114DF171D2073", |
Nobatgeldi
/ JsonExample.scala
Created
February 3, 2022 23:58
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| package org.nobatgeldi | |
| import os.Path | |
| import upickle.default._ | |
| case class TrendyolMarket(name: String, id: Int, address: String) | |
| object JsonExample { | |
| val fileJson: Path = os.pwd/"serialized.json" |
Nobatgeldi
/ eager-few-shot-object-detection-with-tensorflow-2-on-tpu.ipynb
Last active
January 3, 2022 20:07
Eager Few Shot Object Detection with TensorFlow 2 on TPU.ipynb
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Nobatgeldi
/ circleci-useful-env-variables-pr.sh
Created
December 7, 2021 03:09
— forked from dianjuar/circleci-useful-env-variables-pr.sh
A set of environment variables related to pull request to use in CircleCI. These are for GitHub provider
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| # Pull Request ID | |
| export BC_PR_ID="${BC_PR_ID:-${CI_PULL_REQUEST##*/}}"; | |
| REPO=$CI_PULL_REQUEST; | |
| REPO=${REPO##https://github.com/}; | |
| REPO=${REPO%%/pull/$BC_PR_ID}; | |
| # Repo Slug | |
| export BC_REPO_SLUG=$REPO; |
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| data_dir = pathlib.Path('datasets/covisart') | |
| batch_size = 32 | |
| img_height = 180 | |
| img_width = 180 | |
| train_ds = tf.keras.preprocessing.image_dataset_from_directory( | |
| data_dir, | |
| validation_split=0.2, | |
| subset="training", | |
| seed=123, |
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| //Jolt input | |
| [ | |
| { | |
| "ID": "1", | |
| "NAME": "Robert Downey Jr." | |
| }, | |
| { | |
| "ID": "2", | |
| "NAME": "Chris Evans" | |
| } |
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| os.system('pip install /kaggle/input/kerasapplications -q') | |
| os.system('pip install /kaggle/input/efficientnet-keras-source-code/ -q --no-deps') | |
| import efficientnet.tfkeras as efn | |
| def create_model(): | |
| model = models.Sequential() | |
| model.add(efn.EfficientNetB3( |
Nobatgeldi
/ tensoflow.py
Created
January 9, 2021 04:02
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| import numpy as np | |
| import pandas as pd | |
| from tensorflow.keras.layers import Dense, Dropout | |
| from tensorflow.keras.applications import EfficientNetB2 | |
| from tensorflow.keras.preprocessing.image import ImageDataGenerator | |
| from tensorflow.keras.models import Sequential | |
| from tensorflow.keras.optimizers import Adam | |
| from tensorflow.keras import layers | |
| from keras.callbacks import EarlyStopping | |
| import tensorflow as tf |
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| unit = player; | |
| simdikiZaman = time; | |
| eskiZaman = time - simdikiZaman; | |
| mesafeText = "Mesafe:"; | |
| toplamMesafe = 0; | |
| onEachFrame | |
| { | |
| simdikiZaman = time; | |
| zaman = time - eskiZaman; |
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| class havelsen_example_qatar_unity; | |
| class cv_qatar_unit_javelin :havelsen_example_qatar_unity | |
| { | |
| displayName = "Qatar Rifleman - AKM / Javelin"; | |
| vehicleClass = qatar_land_vehicles; | |
| weapons[] = | |
| { | |
| "VBS2_akm", | |
| "cv_qatar_javelin", | |
| "Put", |
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