Working environment

.gitignore

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+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+*.egg-info
+.installed.cfg
+*.egg
+MANIFEST

README.md

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+# Action Detection for Sign Language
+---
+This repository houses work that follows a tutorial presented on [YouTube](https://www.youtube.com/watch?v=doDUihpj6ro&t=4444s)
+by Nicholas Renotte.
+
+In its current state, the notebooks inside of this repository have been demonstrated to run in their full capacity as
+of 23 June 2023.
+
+Because the intended/target audience is probably less saavy, I will be descriptive regarding how to get this running.
+
+In order to follow along, you will want to do the following:
+
+1. Ensure that you have a `python 3.8` environment installed. For example:
+
+```bash
+conda create -n your_env_name python=3.8
+```
+
+2. Activate that conda environment:
+
+```bash
+conda activate your_env_name
+```
+
+3. Pip install the repository:
+
+```bash
+pip install -e .
+```
+
+4. Once this is done, you can run:
+
+```bash
+jupyter lab
+```
+
+Which will spin up a `jupyter lab` server on your local host, and from there, you should be off and running.
+
+**NOTE**: If it doesn't work immediately, make sure your notebook is using the appropriate conda environment.
+It should default to the currently active env.
+
+**NOTES**:
+
+
+## Some Notes on Notebook Execution
+```python
+cap = cv2.VideoCapture(0)
+```
+
+* This argument may need changed as it the integer values determines which video device to use.
+* The code ran on a Windows machine (additional work need for WSL setups), and will likely run on Linux/Mac OS
+* The following snippet of code (cell in a notebook), takes time to initialize and will open a video capture window.
+  In order to stop capture, you must press the `q` key.
+
+```python
+cap = cv2.VideoCapture(0)
+# Set mediapipe model 
+with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic:
+    while cap.isOpened():
+
+        # Read feed
+        ret, frame = cap.read()
+
+        # Make detections
+        image, results = mediapipe_detection(frame, holistic)
+        print(results)
+
+        # Draw landmarks
+        draw_styled_landmarks(image, results)
+
+        # Show to screen
+        cv2.imshow('OpenCV Feed', image)
+
+        # Break gracefully
+        if cv2.waitKey(10) & 0xFF == ord('q'):
+            break
+    cap.release()
+    cv2.destroyAllWindows()
+```

pyproject.toml

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+[project]
+name = "adfsl"
+authors = [
+    { name = "Nicholas Renotte" },
+    { name = "Eric Kerecz" },
+]
+
+dependencies = [
+"opencv-python",
+"jupyterlab",
+"matplotlib",
+"mediapipe",
+"numpy",
+"opencv-python",
+"scikit-learn",
+"tensorflow-cpu==2.4.1",
+#"tensorflow-gpu=2.4.1",
+]
+requires-python = ">=3.8"
+dynamic = ["version"]
+
+[project.urls]
+Soruce = "https://github.com/nicknochnack/ActionDetectionforSignLanguage"

setup.py

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+from setuptools import setup
+
+setup()

src/ActionDetectionforSignLanguage/version.py

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+__version__="0.0.1"