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+# Blood Cancer Detection with YOLOV5
+
+# Intrudiction
+
+This notes that I took for target detection with yolov5. In this project, blood cancer cells were detected.
+
+<img src="https://github.com/safakgunes/Blood-Cancer-Detection-YOLOV5/blob/main/yolov5/runs/train/exp/val_batch1_pred.jpg?raw=true" alt="prediction" width="600"/>
+
+## Create an environment
+
+* Update pip with the following command.
+```bash
+$ python -m pip install --upgrade pip
+```
+* Create an enviroment.
+```bash 
+$ conda create --name yolov5 
+```
+* Activate this environment
+```bash
+$ conda activate yolov5
+```
+## Requirements
+
+* Open the yolov5 directory
+```bash
+$ cd <yolov5_dir>
+```
+* Setup requirements
+```bash
+ $ pip install -r requirements.txt
+```
+* Make sure you have cuda and cudnn installs
+
+## Train
+
+* Make sure environment activated. Go to yolov5 directory.
+```bash
+$ cd <yolov5_dir>
+```
+
+* Run commands below
+```bash
+% python train.py --img 416 --data ../data.yaml --cfg ./models/yolov5s.yaml  --batch 32 --epochs 50
+```
+* You can see the training results and  weights, enter the directory below in the yolov5 folder.
+
+```bash
+$ cd <yolov5_dir>/runs/train
+```
+## Detect
+
+* Run commands below
+
+```bash
+$ python detect.py --source ../dataset/test/images/ --weights ./runs/train/exp/weights/best.pt --conf 0.4
+```                                 
+*  You can see the detection results, enter the directory below in the yolov5 folder.     
+
+```bash
+$ cd <yolov5_dir>/runs/detect
+```