Update install instructions

README.md

@@ -12,6 +12,13 @@ The KABR tools used in this process can be installed with:
 ```
 pip install git+https://github.com/Imageomics/kabr-tools
 ```
+
+**Notes:**
+ - detectron2 requires Linux or MacOS.
+ - If building detectron2's wheel fails, loading a different gnu module may help (`module load gnu/11.2.0`).
+ - If `ModuleNotFoundError: No module named 'torch'` appears, try `pip install torch torchvision` in your environment and try installing `kabr_tools` again.
+ - SlowFast's setup.py is outdated; our workaround is `pip install git+https://github.com/Imageomics/SlowFast@797a6f3ae81c49019d006296f1e0f84f431dc356`, which is included when installing `kabr_tools`.
+
 Each KABR tool can be run through the command line (as described below) or imported as a python module. They each have help information which can be accessed on the command line through `<tool-name> -h`.
 
 Please refer to our [KABR Project Page](https://kabrdata.xyz/) for additional details.
@@ -88,26 +95,8 @@ You can use the [KABR model](https://huggingface.co/imageomics/x3d-kabr-kinetics
 
 To use the [KABR model](https://huggingface.co/imageomics/x3d-kabr-kinetics), download `checkpoint_epoch_00075.pyth.zip`, unzip `checkpoint_epoch_00075.pyth`, and install [SlowFast](https://github.com/facebookresearch/SlowFast). Then run [miniscene2behavior.py](miniscene2behavior.py).
 
-Installing detectron2 and pytorchvideo can be tricky. This should work:
-```
-python -m pip install git+https://github.com/facebookresearch/detectron2.git@2a420edb307c9bdf640f036d3b196bed474b8593
-python -m pip install git+https://github.com/facebookresearch/pytorchvideo.git@1fadaef40dd393ca09680f55582399f4679fc9b7
-```
-
-[SlowFast](https://github.com/facebookresearch/SlowFast)'s `setup.py` is outdated, so a workaround is:
-
-```
-python -m pip install git+https://github.com/zhong-al/SlowFast@797a6f3ae81c49019d006296f1e0f84f431dc356
-```
-
-After [SlowFast](https://github.com/facebookresearch/SlowFast) is installed, you are ready to label the mini-scenes:
-
-```
-miniscene2behavior [--config path_to_config] --checkpoint path_to_checkpoint [--gpu_num number_of_gpus] --miniscene path_to_miniscene [--output path_to_output_csv]
-```
 
 **Notes:**
- - If building detectron2's wheel fails, loading a different gnu module may help (`module load gnu/11.2.0`)
  - If the config hasn't been extracted yet, the script will write it to `config`. 
  - `checkpoint` should be the path to `checkpoint_epoch_00075.pyth`. 
  - If `gpu_num` is 0, the model will use CPU. Using at least 1 GPU greatly increases inference speed. If you're using OSC, you can request a node with one GPU by running `sbatch -N 1 --gpus-per-node 1 -A [account] --time=[minutes] [bash script]`.

pyproject.toml

@@ -37,7 +37,7 @@ dependencies = [
     "pandas",
     "detectron2 @ git+https://github.com/facebookresearch/detectron2.git@2a420edb307c9bdf640f036d3b196bed474b8593",
     "pytorchvideo @ git+https://github.com/facebookresearch/pytorchvideo.git@1fadaef40dd393ca09680f55582399f4679fc9b7",
-    "slowfast @ git+https://github.com/zhong-al/SlowFast@797a6f3ae81c49019d006296f1e0f84f431dc356"
+    "slowfast @ git+https://github.com/Imageomics/SlowFast@797a6f3ae81c49019d006296f1e0f84f431dc356"
 ]
 keywords = [
     "annotation",