Init commit

.github/workflows/pylint.yml

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+name: Pylint
+
+on: [push]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.10"]
+    steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v3
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install pylint
+    - name: Analysing the code with pylint
+      run: |
+        pylint $(git ls-files '*.py')

.gitignore

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+__pycache__
+object_detection/PennFudanPed
+env/
+object_detection/PASCAL_VOC
+object_detection/__pycache__
+object_detection/wandb/
+object_detection/wandb
+tinygrad/
+tinygrad

.gitmodules

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+[submodule "yolov5-arm-custom"]
+	path = yolov5-arm-custom
+	url = git@github.com:alexmehta/yolov5-arm-custom.git

.vscode/settings.json

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+{
+    "python.linting.pylintEnabled": true,
+    "python.linting.enabled": true
+}

README.md

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+# [Theia Project](https://theiaproject.org/)
+
+Theia is an assistance program for the visually impaired that uses a series of sounds to communicate an environment. Theia won multiple awards at local and state science fairs and has a [preprint](https://arxiv.org/abs/2303.13536) and a
+[Video Demo](https://www.youtube.com/watch?v=YrfPQbwcvGg)
+
+## Installation
+
+Clone this repository and install required packages. 
+
+```bash
+pip install -r requirements.txt
+```
+## Hardware 
+
+
+![Incredible Elzing](https://user-images.githubusercontent.com/53285116/229959485-268a7cb2-9581-4d51-b61f-cc5bc89715a6.png)
+
+
+This can be ran on a raspberry pi and uses an intel realsense camera. Refer to those forums/repos for assistance on installing if the script fails. 
+
+To create the device hardware, simply use our provided design [files](https://www.tinkercad.com/things/4GQu8c6IceX-incredible-elzing/edit?sharecode=XYjBHOiL1nd_b_Auc66811gDvaCp-DPv9n27AOGb8Ak).
+
+![image](https://user-images.githubusercontent.com/53285116/229959522-f1a8d1ef-2199-4443-bb5e-cf29cc4e1c1f.png)
+
+
+
+
+
+
+
+## Contributing
+
+Pull requests are welcome. For major changes, please open an issue first
+to discuss what you would like to change.
+
+Please make sure to update any tests as appropriate.
+
+## License
+
+GNU Affero General Public License v3.0
+

classes.yml

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+# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# COCO128-seg dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
+# Example usage: python train.py --data coco128.yaml
+# parent
+# ├── yolov5
+# └── datasets
+#     └── coco128-seg  ← downloads here (7 MB)
+
+
+# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
+path: ../datasets/coco128-seg  # dataset root dir
+train: images/train2017  # train images (relative to 'path') 128 images
+val: images/train2017  # val images (relative to 'path') 128 images
+test:  # test images (optional)
+
+# Classes
+names:
+  0: person
+  1: bicycle
+  2: car
+  3: motorcycle
+  4: airplane
+  5: bus
+  6: train
+  7: truck
+  8: boat
+  9: traffic light
+  10: fire hydrant
+  11: stop sign
+  12: parking meter
+  13: bench
+  14: bird
+  15: cat
+  16: dog
+  17: horse
+  18: sheep
+  19: cow
+  20: elephant
+  21: bear
+  22: zebra
+  23: giraffe
+  24: backpack
+  25: umbrella
+  26: handbag
+  27: tie
+  28: suitcase
+  29: frisbee
+  30: skis
+  31: snowboard
+  32: sports ball
+  33: kite
+  34: baseball bat
+  35: baseball glove
+  36: skateboard
+  37: surfboard
+  38: tennis racket
+  39: bottle
+  40: wine glass
+  41: cup
+  42: fork
+  43: knife
+  44: spoon
+  45: bowl
+  46: banana
+  47: apple
+  48: sandwich
+  49: orange
+  50: broccoli
+  51: carrot
+  52: hot dog
+  53: pizza
+  54: donut
+  55: cake
+  56: chair
+  57: couch
+  58: potted plant
+  59: bed
+  60: dining table
+  61: toilet
+  62: tv
+  63: laptop
+  64: mouse
+  65: remote
+  66: keyboard
+  67: cell phone
+  68: microwave
+  69: oven
+  70: toaster
+  71: sink
+  72: refrigerator
+  73: book
+  74: clock
+  75: vase
+  76: scissors
+  77: teddy bear
+  78: hair drier
+  79: toothbrush
+
+
+# Download script/URL (optional)
+download: https://ultralytics.com/assets/coco128-seg.zip

generatesounds.py

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+import pyttsx3
+import json
+
+settingsfile = open('./settings/soundsettings.json')
+settings = json.load(settingsfile)
+
+classes = settings['classes']
+
+engine = pyttsx3.init()
+engine.setProperty("rate", settings['speakingrate'])
+
+
+
+for x in classes:
+    engine.save_to_file(x, "./sounds/"+str(x)+".mp3")
+    engine.runAndWait()
+    print("generated " + str(x));