Updated README.md.

- included updated environment and setup instructions
- shifted data collection part into detail/summary blocks

README.md

@@ -29,6 +29,7 @@ If you find this code useful in your research, please cite:
 ## Getting started
 
 This code was developed on `Ubuntu 20.04 LTS` with Python 3.7, CUDA 11.7 and PyTorch 1.13.1.
+The current `requirements.txt` was set up with Python 3.9, CUDA 11.3, PyTorch 1.12.1.
 
 
 ### 1. Setup environment
@@ -46,12 +47,10 @@ This codebase shares a large part of its base dependencies with [GMD](https://gi
 
 Setup virtual env:
 ```shell
-python3 -m venv .env_condmdi
-source .env_condmdi/bin/activate
-pip uninstall ffmpeg
-pip install spacy
-python -m spacy download en_core_web_sm
-pip install git+https://github.com/openai/CLIP.git
+python3 -m venv .env_condmdi      # pick your preferred name here
+source .env_condmdi/bin/activate  # and use that name in place of .env_condmdi
+pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
+pip install -r requirements.txt   # updated to include spacy and clip configuration
 ```
 
 Download dependencies:
@@ -78,36 +77,40 @@ bash prepare/download_recognition_unconstrained_models.sh
 ### 2. Get data
 There are two paths to get the data:
 
-(a) **Generation only** with pretrained text-to-motion model without training or evaluating
-
-(b) **Get full data** to train and evaluate the model.
-
+<details>
+    <summary><b>(a) **Generation only** with pretrained text-to-motion model without training or evaluating</b></summary>
 
-#### a. Generation only (text only)
+    #### a. Generation only (text only)
 
-**HumanML3D** - Clone HumanML3D, then copy the data dir to our repository:
+    **HumanML3D** - Clone HumanML3D, then copy the data dir to our repository:
 
-```shell
-cd ..
-git clone https://github.com/EricGuo5513/HumanML3D.git
-unzip ./HumanML3D/HumanML3D/texts.zip -d ./HumanML3D/HumanML3D/
-cp -r HumanML3D/HumanML3D diffusion-motion-inbetweening/dataset/HumanML3D
-cd diffusion-motion-inbetweening
-cp -a dataset/HumanML3D_abs/. dataset/HumanML3D/
-```
+    ```shell
+    cd ..
+    git clone https://github.com/EricGuo5513/HumanML3D.git
+    unzip ./HumanML3D/HumanML3D/texts.zip -d ./HumanML3D/HumanML3D/
+    cp -r HumanML3D/HumanML3D diffusion-motion-inbetweening/dataset/HumanML3D
+    cd CondMDI
+    cp -a dataset/HumanML3D_abs/. dataset/HumanML3D/
+    ```
+</details>
 
+<details>
+    <summary><b>(b) **Get full data** to train and evaluate the model.</b></summary>
 
-#### b. Full data (text + motion capture)
+    #### b. Full data (text + motion capture)
 
-**[Important !]**
-Following GMD, the representation of the root joint has been changed from relative to absolute. Therefore, you need to replace the original files and run GMD's version of `motion_representation.ipynb` and `cal_mean_variance.ipynb` provided in `./HumanML3D_abs/` instead to get the absolute-root data.
+    **HumanML3D** - Follow the instructions in [HumanML3D](https://github.com/EricGuo5513/HumanML3D.git),
+    then copy the result dataset to our repository:
 
-**HumanML3D** - Follow the instructions in [HumanML3D](https://github.com/EricGuo5513/HumanML3D.git),
-then copy the result dataset to our repository:
+    **[Important !]**
+    Following GMD, the representation of the root joint has been changed from relative to absolute. Therefore, when setting up HumanML3D, please
+    run GMD's version of `motion_representation.ipynb` and `cal_mean_variance.ipynb` instead to get the absolute-root data. These files are made
+    available in `./dataset/HumanML3D_abs/`.
 
-```shell
-cp -r ../HumanML3D/HumanML3D ./dataset/HumanML3D
-```
+    ```shell
+    cp -r ../HumanML3D/HumanML3D ./dataset/HumanML3D
+    ```
+</details>
 
 ### 3. Download the pretrained models