Yolo object detection (#18)

* yolo object detection initial commit 🎉

* yolo object detection basketball model

* visualizations and download scripts

* more scripts

02_data_science_toolkit/02_yolo_object_detection/download_basketball_model.sh

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+#!/bin/bash
+
+# Download pre-trained model along with sample images and config files
+curl https://yolo-models.s3.us-east-2.amazonaws.com/basketball.zip -o basketball.zip
+unzip basketball.zip
+rm basketball.zip
+
+# Move config and data files
+cp basketball/data/* yolov3/data 
+cp basketball/cfg/* yolov3/cfg 

02_data_science_toolkit/02_yolo_object_detection/download_chess_dataset.sh

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+#!/bin/bash
+
+# Download pre-trained model along with sample images and config files
+curl https://yolo-models.s3.us-east-2.amazonaws.com/chess_dataset.zip -o chess_dataset.zip
+unzip chess_dataset.zip
+rm chess_dataset.zip
+
+# Move config and data files
+cp chess_dataset/data/* yolov3/data 
+cp chess_dataset/cfg/* yolov3/cfg 

02_data_science_toolkit/02_yolo_object_detection/download_chess_model.sh

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+#!/bin/bash
+
+# Download pre-trained model along with sample images and config files
+curl https://yolo-models.s3.us-east-2.amazonaws.com/chess.zip -o chess.zip
+unzip chess.zip
+rm chess.zip
+
+# Move config and data files
+cp chess/data/* yolov3/data 
+cp chess/cfg/* yolov3/cfg 

02_data_science_toolkit/02_yolo_object_detection/download_rolls_model.sh

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+#!/bin/bash
+
+# Download pre-trained model along with sample images and config files
+curl https://yolo-models.s3.us-east-2.amazonaws.com/rolls.zip -o rolls.zip
+unzip rolls.zip
+rm rolls.zip
+
+# Move config and data files
+cp rolls/data/* yolov3/data 
+cp rolls/cfg/* yolov3/cfg 

02_data_science_toolkit/02_yolo_object_detection/setup_yolo_framework.sh

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+#!/bin/bash
+
+# Clone framework
+git clone https://github.com/ultralytics/yolov3.git
+
+# Getting pre-trained weights
+cd ./yolov3
+sh weights/download_yolov3_weights.sh
+
+# Setup virtual env
+sudo apt-get update
+sudo apt-get install unzip
+sudo apt-get install python-dev
+sudo apt-get install python-pip
+sudo apt-get install python3-venv
+python3 -m venv .env 
+source .env/bin/activate 
+pip3 install --upgrade pip
+pip3 install --upgrade setuptools
+pip3 install Cython
+pip3 install numpy
+pip3 install "pillow<7"
+pip3 install -r requirements.txt
+pip3 install torchvision 
+deactivate
+
+echo "*****************************************************************************"
+echo "****** Your environment has been created ******"
+echo "*****************************************************************************"
+echo ""
+echo "If you had no errors, You can proceed to work with your virtualenv as normal."
+echo "(run 'source .env/bin/activate' in your assignment directory to load the venv,"
+echo " and run 'deactivate' to exit the venv. See assignment handout for details.)"