220 points by tensorflow-user 6 months ago flag hide 12 comments
yolo_fan 6 months ago next
This is amazing! I've been waiting for an upgrade in object detection and YOLO v4 is delivering! Super excited to test this out.
hacker_alice 6 months ago next
@yolo_fan Agreed! With YOLO v4 offering improvement in both precision and speed, it must make integrating object detection into applications much more feasible and cost-realistic for many companies.
deeplearningexpert 6 months ago prev next
Indeed, YOLO v4 brings higher accuracy and speed than its predecessor, making it a real game-changer in the field of computer vision.
randomdev12 6 months ago prev next
What tools or libraries do you need to use YOLO v4? How different is its implementation and capabilities from older version?
code_queen 6 months ago next
Hi @randomdev12, to use YOLO v4 you can look into several libraries for deep learning frameworks including: Tensorflow with the Object Detection API, PyTorch with torchvision, and Darknet (cite). Compared to YOLO v3 improvements include higher accuracy with MPS (Mosaic Data Augmentation, Self-Adversarial Training, and Weighted-Biased Loss) while retaining the real-time capability and increasing the speed (cite in the blog)
imai 6 months ago next
Hi @code_queen, that's very informative, I'll definitely check that out! How long would it take for a someone who has a little to no background in deep learning to get acquainted with YOLO v4 and object detection?
izzy 6 months ago next
@imai, while there's not one solid figure for learning YOLO v4 or object detection, it typically takes several weeks to a few months depending on your learning path and commitments. I suggest starting with basic deep learning then exploring datasets, transfer learning, then YOLO v4 itself. Websites like Medium, GitHub, or DataCamp could be a great resource.
eagerlearner 6 months ago prev next
Perfect timing! I am enrolled in a computer vision course and I am looking forward to diving into this new development with YOLO v4. Thank you for sharing HN community!
anonymous 6 months ago prev next
It's good to see that object detection is improving rapidly. Are there any examples of YOLO v4 being implemented to address specific real-world issues? Are there any companies that have expressed interest in incorporating YOLO v4 into their services?
roadrunner 6 months ago next
@anonymous, I saw some cool real-world examples of YOLO v4. One was in agriculture where YOLO v4 could observe crop fields detect and recognize different crop varieties & diseases. (cite) There's also been research on using YOLO v4 for traffic sign detection at intersections (cite). The possibilities seems truly endless!
uxdesigner_2021 6 months ago prev next
As a designer, my own curiosity was sparked by this. Could someone ELI5 what object detection is and how YOLO v4 different? What are the field applications of this?
vision_pro 6 months ago next
@UXdesigner_2021, Sure, I'll explain in the simplest terms. Object detection is a computer vision technique that detects specific objects within an image or video, such as people, animals, or cars. YOLO v4 is one such method which uses deep learning to perform object detection with higher accuracy and speed than previous versions. Applications vary from vehicle detection in self-driving cars, to security monitoring, and even facial/expression recognition in video conferencing. Take a look at the following resources (cite) to get started!