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| from pathlib import Path | |
| import hashlib | |
| from PIL import Image | |
| def _image_rgb_hash(path: Path) -> str: | |
| """Compute a deterministic SHA-256 hash from the image RGB data.""" | |
| with Image.open(path) as img: | |
| rgb_img = img.convert("RGB") | |
| pixel_bytes = rgb_img.tobytes() |
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| grep -h -o '^[0-9]\+' *.txt | sort -n | uniq -c | sort -k2 -n |
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| { | |
| "name": "Camera FFmpeg", | |
| "cameras": [ | |
| { | |
| "name": "bambu", | |
| "videoConfig": { | |
| "source": "-rtsp_transport tcp -i rtsps://bblp:<LAN mode access code>@<X1C IP address>:322/streaming/live/1" | |
| } | |
| } | |
| ] |
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| *.env | |
| wandb/ | |
| .ipynb_checkpoints/ | |
| *.png | |
| *.ckpt | |
| *.env | |
| **/.DS_Store |
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| // ==UserScript== | |
| // @name subreddit_blocker | |
| // @description Hides all posts from subreddits by name (not case sensitive) or by regex. | |
| // @author khlam | |
| // @match http://*.reddit.com/* | |
| // @match https://*.reddit.com/* | |
| // @version 0.0 | |
| // ==/UserScript== | |
| const regex = [] // your regex block here, comma seperated. |
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| // ==UserScript== | |
| // @name subreddit_custom_css_block | |
| // @version 0.0 | |
| // @description Removes subreddit custom css for old.reddit.com | |
| // @author khlam | |
| // @match http://*.reddit.com/* | |
| // @match https://*.reddit.com/* | |
| // @require https://gist.githubusercontent.com/khlam/f85ee658005a45a99ba0147124c09c38/raw/704f92f52d7c4c1ed8e71f2c9311b46c2e6ea3cc/jQuery.v3.6.0 | |
| /* globals jQuery, $ */ | |
| // @run-at document-end |
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| // ==UserScript== | |
| // @name twitch_front_carousel_block | |
| // @version 0.0 | |
| // @description Blocks twitch frontpage autoplaying stream by setting its source to null. | |
| // @author khlam | |
| // @match http://www.twitch.tv/ | |
| // @match https://www.twitch.tv/ | |
| // @grant none | |
| // @run-at document-end | |
| // ==/UserScript== |
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| abandoned | |
| able | |
| absolute | |
| adorable | |
| adventurous | |
| academic | |
| acceptable | |
| acclaimed | |
| accomplished | |
| accurate |
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| import numpy as np | |
| import pandas as pd | |
| import torch | |
| from torch.utils.data import Dataset, DataLoader | |
| class lazyLoadCSVDataset(Dataset): | |
| def __init__(self, data_CSV_path, rows_each_fetch=500, shuffle=True): | |
| self.dataPath = data_CSV_path |