Create README.md

README.md

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+---
+# For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
+{}
+---
+
+# Dataset Card for DLC Speed Benchmarking ZIP
+
+This supports the dlc-live benchmarking [zip](https://github.com/DeepLabCut/DeepLabCut-live/blob/427c12609307ef685e4193c91026567308820cbe/dlclive/benchmark.py#L40) formally hosted on our Harvard Rowland server. 
+All information can be found in our publication:
+
+Real-time, low-latency closed-loop feedback using markerless posture tracking
+Gary A Kane, Gonçalo Lopes, Jonny L Saunders, Alexander Mathis, Mackenzie W Mathis 
+https://elifesciences.org/articles/61909
+
+
+
+### Direct Use
+
+```python
+"""
+DeepLabCut Toolbox (deeplabcut.org)
+© A. & M. Mathis Labs
+
+Licensed under GNU Lesser General Public License v3.0
+"""
+
+# Script for running the official benchmark from Kane et al, 2020.
+# Please share your results at https://github.com/DeepLabCut/DLC-inferencespeed-benchmark
+
+import os, pathlib
+import glob
+
+from dlclive import benchmark_videos, download_benchmarking_data
+
+datafolder = os.path.join(
+    pathlib.Path(__file__).parent.absolute(), "Data-DLC-live-benchmark"
+)
+
+if not os.path.isdir(datafolder):  # only download if data doesn't exist!
+    # Downloading data.... this takes a while (see terminal)
+    download_benchmarking_data(datafolder)
+
+n_frames = 10000  # change to 10000 for testing on a GPU!
+pixels = [2500, 10000, 40000, 160000, 320000, 640000]
+
+dog_models = glob.glob(datafolder + "/dog/*[!avi]")
+dog_video = glob.glob(datafolder + "/dog/*.avi")[0]
+mouse_models = glob.glob(datafolder + "/mouse_lick/*[!avi]")
+mouse_video = glob.glob(datafolder + "/mouse_lick/*.avi")[0]
+
+this_dir = os.path.dirname(os.path.realpath(__file__))
+# storing results in /benchmarking/results: (for your PR)
+out_dir = os.path.normpath(this_dir + "/results")
+
+if not os.path.isdir(out_dir):
+    os.mkdir(out_dir)
+
+for m in dog_models:
+    benchmark_videos(m, dog_video, output=out_dir, n_frames=n_frames, pixels=pixels)
+
+for m in mouse_models:
+    benchmark_videos(m, mouse_video, output=out_dir, n_frames=n_frames, pixels=pixels)
+```