Update readme and installation docs

- removed poetry instructions
- added optional instructions for installation with uv
- added notes on tensorflow support for windows

Author: deruyter92

README.md

@@ -65,20 +65,29 @@ https://www.rts.ch/play/radio/cqfd/audio/capturer-les-mouvements-des-animaux-en-
 
 ### Installation
 
-Please see our instruction manual to install on a [Windows or Linux machine](
+DeepLabCut-live can be installed from PyPI with PyTorch or Tensorflow directly: 
+   ```bash
+   # With PyTorch (recommended)
+   pip install deeplabcut-live[pytorch]
+   
+   # Or with TensorFlow
+   pip install deeplabcut-live[tf]
+   
+   # Or using uv
+   uv pip install deeplabcut-live[pytorch] # or [tf]
+   ```
+
+Please see our instruction manual for more elaborate information on how to install on a [Windows or Linux machine](
 docs/install_desktop.md) or on a [NVIDIA Jetson Development Board](
 docs/install_jetson.md). Note, this code works with PyTorch, TensorFlow 1 or TensorFlow
 2 models, but whatever engine you exported your model with, you must import with the 
 same version (i.e., export a PyTorch model, then install PyTorch, export with TF1.13, 
 then use TF1.13 with DlC-Live; export with TF2.3, then use TF2.3 with DLC-live).
 
-- available on pypi as: `pip install deeplabcut-live`
-  
+Note, you can test your installation by running:
 
-Note, you can then test your installation by installing poetry (`pip install poetry`), then running:
-
-```python
-poetry run dlc-live-test
+```bash
+dlc-live-test
 ```
 
 If installed properly, this script will i) create a temporary folder ii) download the

docs/install_desktop.md

@@ -1,47 +1,91 @@
-### Install DeepLabCut-live on a desktop (Windows/Ubuntu)
+# Installation Guide
 
-We recommend that you install DeepLabCut-live in a conda environment (It is a standard
-python package though, and other distributions will also likely work). In this case,
-please install [Miniconda](https://docs.anaconda.com/miniconda/miniconda-install/) 
-(recommended) or Anaconda.
+DeepLabCut-live can be installed using several methods. **For most users, we recommend installing from PyPI using `uv` or `pip`** - this is the simplest and most reliable method.
 
-If you have an Nvidia GPU and want to use its capabilities, you'll need to [install CUDA
-](https://developer.nvidia.com/cuda-downloads) first (check that CUDA is installed - 
-checkout the installation guide for [linux](
-https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html) or [Windows](
-https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html).
 
-Create a conda environment with python 3.10 or 3.11, and install 
-[`pytables`](https://www.pytables.org/usersguide/installation.html), `torch` and 
-`torchvision`. Make sure you [install the correct `torch` and `torchvision` versions
-for your compute platform](https://pytorch.org/get-started/locally/)!
 
-```
-conda create -n dlc-live python=3.11 
-conda activate dlc-live
-conda install -c conda-forge pytables==3.8.0
+## System Requirements
 
-# Installs PyTorch on Linux with CUDA 12.4
-pip install torch torchvision --index-url https://download.pytorch.org/whl/cu124
-```
+- Python 3.10, 3.11, or 3.12
+- For GPU support: CUDA-compatible NVIDIA GPU (see [CUDA installation guide](https://developer.nvidia.com/cuda-downloads))
 
-Activate the conda environment, install the DeepLabCut-live package, then test the
-installation:
 
-```
-conda activate dlc-live
-pip install deeplabcut-live
-dlc-live-test
-```
+### Important Notes
+
+- **Required dependencies**: You must install either PyTorch or TensorFlow. Choose the one that matches your exported model:
+  - PyTorch models: Use `deeplabcut-live[pytorch]`
+  - TensorFlow models: Use `deeplabcut-live[tf]`
+- **Tensorflow support**: Tensorflow is not supported for python versions >=3.11 on Windows machines, please use python 3.10 instead.
+- **Conda environments**: When using `pip`, it's recommended to install in a separate conda environment to avoid dependency conflicts.
+- **uv sync**: If you have cloned the repository and are using `uv`, you can use `uv sync --extra pytorch` (or `--extra tf`) to install all dependencies automatically.
+
+## 1. Quick Start (recommended)
+
+Install from PyPI with PyTorch or TensorFlow:
+   ```bash
+   # With PyTorch (recommended)
+   pip install deeplabcut-live[pytorch]
+   
+   # Or with TensorFlow
+   pip install deeplabcut-live[tf]
+   
+   # Or using uv
+   uv pip install deeplabcut-live[pytorch] # or [tf]
+   ```
+
+## 2. Install from Git Repository
+If you want to install from a local clone of the repository, follow these steps:
+
+1. Clone the repository:
+   ```bash
+   git clone https://github.com/DeepLabCut/DeepLabCut-live.git
+   cd DeepLabCut-live
+   ```
+
+2. Install in editable mode:
 
-Note, you can also just run the test:
+    **Option A - with uv (recommended; fastest & dependencies are handled automatically)**
+   ```bash
+   # Using uv
+   uv sync --extra pytorch --python 3.11 # or --extra tf for TensorFlow
+   ```
+   
+   **Option B - using pip in a conda environment**
+   ```
+   conda create -n dlc-live python=3.11
+   conda activate dlc-live
+   pip install -e ".[pytorch]"  # or ".[tf]" for TensorFlow
+   ```
 
-`dlc-live-test`
+## 3. Separate Pytorch or Tensorflow installation
+If the above instructions do not work, or you want to use a specific Pytorch or Tensorflow version. You can first install Pytorch or Tensorflow separately.
+   ```
+   # Install Pytorch
+   pip install torch torchvision --index-url https://download.pytorch.org/whl/cu124
+   
+   # Or install TensorFlow instead
+   pip install tensorflow
+   ```
+and then install DeepLabCut-live following the instructions in option 1. or 2. above.
+
+## How to install uv or Conda?
+- **uv**: See more information on the website  [here](https://docs.astral.sh/uv/#installation). The basic installation commands are:
+    - for Linux/macOS: `curl -LsSf https://astral.sh/uv/install.sh | sh`
+    - for Windows: `powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"`
+- **conda**: Follow the instructions [here](https://docs.anaconda.com/miniconda/miniconda-install/).
+
+
+
+
+## Verify DeepLabCut-live Installation
+
+Test your installation by running:
+
+```bash
+dlc-live-test
+```
 
 If installed properly, this script will i) create a temporary folder ii) download the
 full_dog model from the [DeepLabCut Model Zoo](
 http://www.mousemotorlab.org/dlc-modelzoo), iii) download a short video clip of
-a dog, and iv) run inference while displaying keypoints. v) remove the temporary folder.
-
-Please note, you also should have curl installed on your computer (typically this is
-already installed on your system), but just in case, just run `sudo apt install curl`
+a dog, and iv) run inference while displaying keypoints. v) remove the temporary folder.