krishnaik06 · yashh2417 · May 16, 2024
diff --git a/ML Projects/Drowsiness/Drowsiness.ipynb b/ML Projects/Drowsiness/Drowsiness.ipynb
diff --git a/ML Projects/Drowsiness/README.md b/ML Projects/Drowsiness/README.md
@@ -0,0 +1,248 @@
+
+# Drowsiness Detection Android App 
+## Train Custom Dataset
+
+📚 This guide explains how to train your own custom dataset with YOLOv5 🚀. See YOLOv5 Docs for additional details. UPDATED 13 April 2023.
+
+To understand the code head to this [video](https://youtu.be/HH0KresgvNc?si=ZgVRUC6PS_Wn0YjG) where i am [Describing Drowsiness Detection Android App's Code](https://youtu.be/HH0KresgvNc?si=ZgVRUC6PS_Wn0YjG).
+
+## Before You Start
+Clone repo and install requirements.txt in a Python>=3.7.0 environment, including PyTorch>=1.7. Models and datasets download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
+
+```
+git clone https://github.com/ultralytics/yolov5  # clone
+cd yolov5
+pip install -r requirements.txt  # install
+```
+## Train On Custom Data
+![alt text](https://raw.githubusercontent.com/ultralytics/assets/main/im/integrations-loop.png)
+
+Creating a custom model to detect your objects is an iterative process of collecting and organizing images, labeling your objects of interest, training a model, deploying it into the wild to make predictions, and then using that deployed model to collect examples of edge cases to repeat and improve.
+## 1. Create Dataset
+YOLOv5 models must be trained on labelled data in order to learn classes of objects in that data. There are two options for creating your dataset before you start training:
+## 1.1 Collect Images
+Your model will learn by example. Training on images similar to the ones it will see in the wild is of the utmost importance. Ideally, you will collect a wide variety of images from the same configuration (camera, angle, lighting, etc.) as you will ultimately deploy your project.
+
+If this is not possible, you can start from [a public dataset](https://universe.roboflow.com/?ref=ultralytics). to train your initial model and then [sample images from the wild during inference](https://blog.roboflow.com/computer-vision-active-learning-tips/?ref=ultralytics) to improve your dataset and model iteratively.
+## 1.2 Create Labels
+Once you have collected images, you will need to annotate the objects of interest to create a ground truth for your model to learn from.
+
+LabelImg is a graphical image annotation tool.
+
+It is written in Python and uses Qt for its graphical interface.
+
+Annotations are saved as XML files in PASCAL VOC format, the format used
+by [ImageNet](http://www.image-net.org).  Besides, it also supports YOLO and CreateML formats.
+
+![image](https://raw.githubusercontent.com/yashh2417/faltu/main/label-name.png)
+
+![image](https://raw.githubusercontent.com/yashh2417/faltu/main/label-name1.png)
+
+[Watch a demo video](https://youtu.be/p0nR2YsCY_U)
+
+## Installation
+------------------
+
+### Get from PyPI but only python3.0 or above
+
+This is the simplest (one-command) install method on modern Linux distributions such as Ubuntu and Fedora.
+
+```
+    pip3 install labelImg
+    labelImg
+    labelImg [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
+```
+
+### Build from source
+
+Linux/Ubuntu/Mac requires at least [Python
+2.6](https://www.python.org/getit) and has been tested with [PyQt
+4.8](https://www.riverbankcomputing.com/software/pyqt/intro). However, [Python3 or above](https://www.python.org/getit/) and  [PyQt5](https://pypi.org/project/PyQt5/) are strongly recommended.
+
+
+## Ubuntu Linux
+
+Python 3 + Qt5
+
+```
+    sudo apt-get install pyqt5-dev-tools
+    sudo pip3 install -r requirements/requirements-linux-python3.txt
+    make qt5py3
+    python3 labelImg.py
+    python3 labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
+```
+## macOS
+
+Python 3 + Qt5
+
+```
+    brew install qt  # Install qt-5.x.x by Homebrew
+    brew install libxml2
+
+    or using pip
+
+    pip3 install pyqt5 lxml # Install qt and lxml by pip
+
+    make qt5py3
+    python3 labelImg.py
+    python3 labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
+```
+## Windows
+
+Install [Python](https://www.python.org/downloads/windows/),
+[PyQt5](https://www.riverbankcomputing.com/software/pyqt/download5) and [install lxml](http://lxml.de/installation.html).
+
+Open cmd and go to the [labelImg](labelimg) directory
+```
+    pyrcc4 -o libs/resources.py resources.qrc
+    For pyqt5, pyrcc5 -o libs/resources.py resources.qrc
+
+    python labelImg.py
+    python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
+```
+You can pull the image which has all of the installed and required dependencies. [Watch a demo video](https://youtu.be/nw1GexJzbCI)
+
+
+## Usage
+
+### Steps (PascalVOC)
+    1. Build and launch using the instructions above.
+    2. Click 'Change default saved annotation folder' in Menu/File
+    3. Click 'Open Dir'
+    4. Click 'Create RectBox'
+    5. Click and release left mouse to select a region to annotate the rect
+    box
+    6. You can use right mouse to drag the rect box to copy or move it
+
+The annotation will be saved to the folder you specify.
+
+You can refer to the below hotkeys to speed up your workflow.
+
+### Steps (YOLO)
+
+
+    1. In ``data/predefined_classes.txt`` define the list of classes that will be used for your training.
+
+    2. Build and launch using the instructions above.
+
+    3. Right below "Save" button in the toolbar, click "PascalVOC" button to switch to YOLO format.
+
+    4. You may use Open/OpenDIR to process single or multiple images. When finished with a single image, click save.
+
+A txt file of YOLO format will be saved in the same folder as your image with same name. A file named "classes.txt" is saved to that folder too. "classes.txt" defines the list of class names that your YOLO label refers to.
+
+Note:
+
+- Your label list shall not change in the middle of processing a list of images. When you save an image, classes.txt will also get updated, while previous annotations will not be updated.
+
+- You shouldn't use "default class" function when saving to YOLO format, it will not be referred.
+
+- When saving as YOLO format, "difficult" flag is discarded.
+
+## 2. Select a Model
+
+Select a pretrained model to start training from. Here we select [YOLOv5s](https://github.com/ultralytics/yolov5/blob/master/models/yolov5s.yaml), the second-smallest and fastest model available. See our README [table](https://github.com/ultralytics/yolov5#pretrained-checkpoints) for a full comparison of all models.
+
+![image](https://user-images.githubusercontent.com/59910227/120440324-6162ce80-c3be-11eb-8e32-2d8be996332b.png)
+
+## 3. Train
+Train a YOLOv5s model on COCO128 by specifying dataset, batch-size, image size and either pretrained --weights yolov5s.pt (recommended), or randomly initialized --weights '' --cfg yolov5s.yaml (not recommended). Pretrained weights are auto-downloaded from the latest [YOLOv5 release](https://github.com/ultralytics/yolov5/releases).
+
+```
+# Train YOLOv5s on COCO128 for 3 epochs
+$ python train.py --img 320  --batch 16 --epochs 100 --data dataset.yaml --weights yolov5s.pt 
+```
+
+💡 ProTip: Add --cache ram or --cache disk to speed up training (requires significant RAM/disk resources).
+
+💡 ProTip: Always train from a local dataset. Mounted or network drives like Google Drive will be very slow.
+
+All training results are saved to runs/train/ with incrementing run directories, i.e. runs/train/exp2, runs/train/exp3 etc. For more details see the Training section of our tutorial notebook
+
+## Load the Custom Model
+```
+model = torch.hub.load('ultralytics/yolov5', 'custom' , path='yolov5/runs/train/exp/weights/best.pt', force_reload= True)
+```
+## Testing
+
+### Testing with folder's images
+Images present in any particular folder will be tested and the result will store to the runs/detect/exp.
+```
+python detect.py --weights runs/train/exp/weights/best.pt --img 320 --conf 0.25 --source runs/train/exp/test_images
+```
+### Testing the Model with Individual image
+Images will be test on the notebook only.
+```
+$ img = os.path.join('data', 'images', 'awake.6ea0bcf6-0c54-11ef-bb9f-be91f5bcaf0b.jpg')
+$ results = model(img)
+$ results.print()
+$ %matplotlib inline
+$ plt.imshow(np.squeeze(results.render()))
+$ plt.show()
+```
+
+![awake](https://raw.githubusercontent.com/yashh2417/faltu/main/awake.6cccfd9a-0c54-11ef-bb9f-be91f5bcaf0b.jpg)
+
+![drowsy](https://raw.githubusercontent.com/yashh2417/faltu/main/drowsy.82177d1a-0c54-11ef-bb9f-be91f5bcaf0b.jpg)
+
+## Real Time Detection
+```
+cap = cv2.VideoCapture(0)
+while cap.isOpened():
+    ret, frame = cap.read()
+    results = model(frame)
+    cv2.imshow('YOLO', np.squeeze(results.render()))
+    if cv2.waitKey(10) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()
+```
+<img src="https://raw.githubusercontent.com/yashh2417/faltu/main/Real-Time%20Detection%202.gif" > 
+
+## Convert the Model into tflite Model
+```
+# Convert weights to fp16 TFLite model
+!cd yolov5 && python export.py --weights runs/train/exp/weights/best.pt --include tflite --img 320
+```
+
+![img](https://raw.githubusercontent.com/yashh2417/faltu/main/yolo-to-tflite.png)
+
+### Testing the tflite model on folder's images
+```
+#After running the above command, you will have best-fp16.tflite in runs\train\exp\weights folder
+
+!cd yolov5 && python detect.py --weights runs/train/exp/weights/best-fp16.tflite --img 320 --conf 0.25 --source runs/train/exp/test_images
+```
+results will store in runs/detect/exp.
+
+## Android App
+You must have android studio to integrate tflite Model with an Android App.
+
+Now, download the android app's code from my [github](https://github.com/yashh2417/Android-App).
+Or you can find it inside the yolov5 folder in this repository.
+
+### Now Put TFLite models in assets folder of Android project, and change
+And then open android/app/src/main/java/org/tensorflow/lite/examples/detection/tflite/DetectorFactory.java
+
+Do the following changes:
+
+    1. Change the inputSize of image as per your dataset.
+
+    2. Change labelFilename according to the classes of the model
+
+    3. Then run the program in Android Studio.
+
+## Run Android App
+
+Go to android/app/src/main/java/org/tensorflow/lite/examples/detection/tflite/DetectorFactory.java and press run in android studio.
+
+![photo](https://raw.githubusercontent.com/yashh2417/faltu/main/Launching%20app%20in%20android%20device.png)
+
+## Real Time Detection in Android App
+
+<img src="https://raw.githubusercontent.com/yashh2417/faltu/main/VID_20240509105056.gif" width="35%">     <img src="https://raw.githubusercontent.com/yashh2417/faltu/main/VID_20240509105129.gif" width="35%">
+
+
+#### by Yash 
+LinkedIn: [yashh2417](https://www.linkedin.com/in/yashh2417/)
diff --git a/ML Projects/Drowsiness/data/labels.cache b/ML Projects/Drowsiness/data/labels.cache
diff --git a/ML Projects/Drowsiness/data/labels/awake.5ff3fdc6-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.5ff3fdc6-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.543359 0.521528 0.202344 0.465278
diff --git a/ML Projects/Drowsiness/data/labels/awake.657e364e-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.657e364e-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.553125 0.280556 0.264062 0.552778
diff --git a/ML Projects/Drowsiness/data/labels/awake.6751d0a2-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.6751d0a2-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.480859 0.252083 0.258594 0.493056
diff --git a/ML Projects/Drowsiness/data/labels/awake.6925b3a8-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.6925b3a8-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.491016 0.272222 0.266406 0.533333
diff --git a/ML Projects/Drowsiness/data/labels/awake.6af97872-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.6af97872-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.519141 0.313194 0.189844 0.493056
diff --git a/ML Projects/Drowsiness/data/labels/awake.6cccfd9a-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.6cccfd9a-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.526953 0.302778 0.200781 0.558333
diff --git a/ML Projects/Drowsiness/data/labels/awake.6ea0bcf6-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.6ea0bcf6-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.528125 0.290972 0.209375 0.529167
diff --git a/ML Projects/Drowsiness/data/labels/awake.7074923c-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.7074923c-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.546484 0.298611 0.210156 0.544444
diff --git a/ML Projects/Drowsiness/data/labels/awake.834d6546-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.834d6546-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.529687 0.456944 0.214062 0.538889
diff --git a/ML Projects/Drowsiness/data/labels/awake.852ff798-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.852ff798-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.528125 0.451389 0.217188 0.505556
diff --git a/ML Projects/Drowsiness/data/labels/awake.8703a0ba-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.8703a0ba-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.534375 0.454861 0.214062 0.534722
diff --git a/ML Projects/Drowsiness/data/labels/awake.88d77574-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.88d77574-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.527344 0.438889 0.218750 0.513889
diff --git a/ML Projects/Drowsiness/data/labels/awake.8aab321e-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.8aab321e-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.520703 0.436111 0.219531 0.527778
diff --git a/ML Projects/Drowsiness/data/labels/awake.8c7f25d2-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.8c7f25d2-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.521484 0.442361 0.221094 0.540278
diff --git a/ML Projects/Drowsiness/data/labels/awake.8e52ebe6-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.8e52ebe6-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.528125 0.449306 0.220312 0.498611
diff --git a/ML Projects/Drowsiness/data/labels/awake.90267fc8-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.90267fc8-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.535156 0.430556 0.215625 0.491667
diff --git a/ML Projects/Drowsiness/data/labels/awake.91fa5b44-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.91fa5b44-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.535547 0.443750 0.213281 0.490278
diff --git a/ML Projects/Drowsiness/data/labels/awake.93ce013c-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.93ce013c-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.535547 0.465278 0.213281 0.544444
diff --git a/ML Projects/Drowsiness/data/labels/awake.e67af8b8-0c54-11ef-a07d-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.e67af8b8-0c54-11ef-a07d-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.548438 0.533333 0.189062 0.475000
diff --git a/ML Projects/Drowsiness/data/labels/awake.e85da5ea-0c54-11ef-a07d-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/awake.e85da5ea-0c54-11ef-a07d-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+15 0.545703 0.518750 0.192969 0.437500
diff --git a/ML Projects/Drowsiness/data/labels/classes.txt b/ML Projects/Drowsiness/data/labels/classes.txt
@@ -0,0 +1,17 @@
+dog
+person
+cat
+tv
+car
+meatballs
+marinara sauce
+tomato soup
+chicken noodle soup
+french onion soup
+chicken breast
+ribs
+pulled pork
+hamburger
+cavity
+awake
+drowsy
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.754d4fec-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.754d4fec-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.517578 0.356944 0.255469 0.666667
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.7720eb80-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.7720eb80-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.610938 0.361111 0.262500 0.658333
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.78f4ab5e-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.78f4ab5e-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.431250 0.348611 0.292187 0.627778
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.7ac8677c-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.7ac8677c-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.460547 0.319444 0.267969 0.602778
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.7c9c1f26-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.7c9c1f26-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.520312 0.286806 0.226562 0.570833
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.7e6ffb2e-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.7e6ffb2e-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.505078 0.284722 0.232031 0.561111
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.80437f3e-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.80437f3e-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.578125 0.279861 0.242188 0.526389
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.82177d1a-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.82177d1a-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.557031 0.341667 0.237500 0.663889
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.83eb2484-0c54-11ef-bb9f-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.83eb2484-0c54-11ef-bb9f-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.481250 0.337500 0.282813 0.655556
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.98a6cd06-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.98a6cd06-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.532031 0.531250 0.262500 0.726389
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.9a7a4234-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.9a7a4234-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.444531 0.528472 0.296875 0.631944
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.9c4e39d0-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.9c4e39d0-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.582812 0.512500 0.281250 0.666667
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.9e21f5c6-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.9e21f5c6-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.575391 0.529861 0.252344 0.693056
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.9ff5bdec-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.9ff5bdec-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.622656 0.552778 0.246875 0.647222
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.a1c97046-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.a1c97046-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.665234 0.560417 0.296094 0.643056
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.a39d0d60-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.a39d0d60-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.473047 0.536806 0.280469 0.651389
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.a570ffb6-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.a570ffb6-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.520312 0.466667 0.220312 0.500000
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.a744d13c-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.a744d13c-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.537109 0.463194 0.221094 0.551389
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.a9188292-0c4a-11ef-babd-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.a9188292-0c4a-11ef-babd-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.558594 0.529861 0.234375 0.662500
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.ed367fce-0c54-11ef-a07d-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.ed367fce-0c54-11ef-a07d-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.434375 0.588889 0.259375 0.530556
diff --git a/ML Projects/Drowsiness/data/labels/drowsy.ef0a076c-0c54-11ef-a07d-be91f5bcaf0b.txt b/ML Projects/Drowsiness/data/labels/drowsy.ef0a076c-0c54-11ef-a07d-be91f5bcaf0b.txt
@@ -0,0 +1 @@
+16 0.629297 0.549306 0.250781 0.565278
diff --git a/ML Projects/Drowsiness/labelImg/CONTRIBUTING.rst b/ML Projects/Drowsiness/labelImg/CONTRIBUTING.rst
@@ -0,0 +1,3 @@
+TzuTa Lin
+[LabelMe](http://labelme2.csail.mit.edu/Release3.0/index.php)
+Ryan Flynn