Ultimate Guide to Setting Up YOLOv5 on macOS for Object Detection
Learn how to set up YOLOv5 on your Mac for advanced object detection using PyTorch and Torch. Follow the steps to install necessary packages, clone repositories, and run detection scripts efficiently. Explore the world of YOLOv5 and start detecting objects today!
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Presentation Transcript
2021 For Mac YOLOv5
MAC Python 3.8 python.org mac https://www.python.org/downloads/release/python-388/
1. project YOLOCOCO 2. install torch 3. git clone labelImg 4. git clone yolov5 5. yolo5 requirements.txt 6. detect00.py 7. detect01.py 8. detect02.py
1.project YOLOCOCO (data/images)
PyTorch Facebook 2017 Torch Python Python Python PyTorch https://reurl.cc/8375Yg
https://pytorch.org/get-started/locally/ Mac pip3 install torch torchvision torchaudio -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
ternimal git clone https://github.com/tzutalin/labelImg
ternimal git clone https://github.com/ultralytics/yolov5
ternimal cd yolov5 pip install -r requirements.txt
import torch import cv2 import numpy as np model = torch.hub.load('ultralytics/yolov5', 'yolov5s') # print(model) img=cv2.imread('IMG_2997.JPG') results = model(img) results.print() print(results.xyxy) cv2.imshow('YOLO COCO', np.squeeze(results.render())) cv2.waitKey(0)
import torch import numpy as np import cv2 model = torch.hub.load('ultralytics/yolov5', 'yolov5s') cap = cv2.VideoCapture(0) while cap.isOpened(): success, frame = cap.read() if not success: print("Ignoring empty camera frame.") continue results = model(frame) cv2.imshow( YOLO COCO 01', np.squeeze(results.render())) if cv2.waitKey(1) & 0xFF == 27: break cap.release() cv2.destroyAllWindows()
import torch import numpy as np import cv2 import time prev_time = 0 model = torch.hub.load('ultralytics/yolov5', 'yolov5s') cap = cv2.VideoCapture("https://cctvn.freeway.gov.tw/abs2mjpg/bmjpg?camera=13380") while cap.isOpened(): success, frame = cap.read() if not success: print("Ignoring empty camera frame.") continue frame = cv2.resize(frame,(960,540)) results = model(frame) output_image = np.squeeze(results.render()) cv2.putText(output_image, f'FPS: {int(1 / (time.time() - prev_time))} , (3, 40), cv2.FONT_HERSHEY_PLAIN, 3, (0, 0, 255), 3) prev_time = time.time() cv2.imshow('YOLO COCO 02', output_image) if cv2.waitKey(1) & 0xFF == 27: break cap.release() cv2.destroyAllWindows()
import pafy url = "https://www.youtube.com/watch?v=r9dlwCs4JmE" # url = "https://www.youtube.com/watch?v=E87M8LRlnKQ" live = pafy.new(url) stream = live.getbest(preftype="mp4") cap = cv2.VideoCapture(stream.url)
=== pafy youtube-dl === 1. pycharm pafy 2. pycharm Youtube-dl2 3. pycharm terminal pip install -U youtube-dl Mac terminal open "/Applications/Python 3.8/Install Certificates.command"
