#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
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#PHA/USDT analysis :
#PHA has experienced a breakout followed by a retest of the support zone. The price is now anticipated to continue its downward trajectory and test lower levels. This bearish outlook is supported by the breakout and retest pattern, suggesting a potential continuation of the downtrend.
TF : 4H
Entry : $0.1465
Target : $0.1146
SL : $0.1642