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Source channel @githubtrending · Post #14949 · Jul 12

#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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Crypto M - Crypto News

@CryptoM · Post #64877 · 04/10/2026, 06:14 AM

🚀 Starknet Opens Voting on v0.14.2 Upgrade Proposal Starknet has announced that voting is now open for STRK holders on the v0.14.2 upgrade proposal. According to Foresight News, the voting period will end on April 16. The proposed upgrade includes the introduction of SNIP-36, SNIP-37, and SNIP-13, and aims to enable protocol-level S-Two proof verification, significantly reducing costs for privacy use cases and zk-thread applications. Additionally, the upgrade seeks to adjust the storage economic model to more accurately reflect network resource usage while maintaining cost advantages for developers. The StarkGate token contract will also be upgraded to optimize ERC-20 event indexing, verification, and token handling. Other internal upgrades are planned to prepare for the decentralized verification phase described in SNIP-33, including improvements in P2P, weighted proposer sampling, and the concept of virtual proposers. #Starknet#STRK#v0.14.2 #SNIP36#SNIP37#SNIP13#STwoProof#PrivacyUseCases#zkThread#StorageEconomicModel#StarkGate#ERC20#P2P#DecentralizedVerification#SNIP33#VirtualProposers