#jupyter_notebook#darknet#pytorch#scaled_yolov4#yolor#yolov3#yolov4#yolov7
YOLOv7 is a powerful tool for detecting objects in images and videos. It is fast, accurate, and can work well on devices with limited power, making it useful for real-time applications like self-driving cars and surveillance systems. YOLOv7 uses advanced techniques like Feature Pyramid Networks to detect objects of different sizes and can handle complex scenes with overlapping objects. This makes it beneficial for users who need quick and precise object detection in various environments.
https://github.com/WongKinYiu/yolov7
🪙 32,137 #BTC ($2.18 billion) went from the wallet of the #Mt․Gox exchange that collapsed in 2014 to an unknown address — the market reacted with a drop, suggesting that payments to the exchange's creditors could begin at any moment.
⚫️The Black Swan arrived unexpectedly... wait for new comments, despite the unpleasant surprise, the situation may become an opportunity to enter the market and make money on non-negative growth.
😙 The reasons for the fall of the # bitcoin exchange rate below $61,000
The unemployment rate was 4.3%, which is higher than expected, indicating a possible recession
The Bank of Japan raised the interest rate for the first time in 17 years, which led to an outflow of investments from risky assets
Increased geopolitical tensions (fear of a major world war)
😏Continued distribution of #BTC from #Mt.Gox and #Genesis