Showing 4 open source projects for "yolov4.weights"

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  • 1
    NetworkX

    NetworkX

    Network analysis in Python

    ...Generators for classic graphs, random graphs, and synthetic networks. Nodes can be "anything" (e.g., text, images, XML records). Edges can hold arbitrary data (e.g., weights, time-series). Open source 3-clause BSD license. Well tested with over 90% code coverage. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. Find the shortest path between two nodes in an undirected graph. Python’s None object is not allowed to be used as a node. It determines whether optional function arguments have been assigned in many functions. ...
    Downloads: 4 This Week
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  • 2
    EPLB

    EPLB

    Expert Parallelism Load Balancer

    ...It uses policies like hierarchical load balancing (grouped experts placed at node and then GPU level) and global load balancing depending on configuration. The logic is implemented in eplb.py and supports predicting placements given estimated expert usage weights. EPLB aims to reduce hot-spotting and ensure more uniform usage of compute resources in large MoE deployments.
    Downloads: 0 This Week
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  • 3
    Age and Gender Estimation

    Age and Gender Estimation

    Keras implementation of a CNN network for age and gender estimation

    ...In training, the IMDB-WIKI dataset is used. Because the face images in the UTKFace dataset is tightly cropped (there is no margin around the face region), faces should also be cropped in demo.py if weights trained by the UTKFace dataset is used. Please set the margin argument to 0 for tight cropping. You can evaluate a trained model on the APPA-REAL (validation) dataset. We pose the age regression problem as a deep classification problem followed by a softmax expected value refinement and show improvements over direct regression training of CNNs. ...
    Downloads: 3 This Week
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  • 4
    ENAS in PyTorch

    ENAS in PyTorch

    PyTorch implementation of "Efficient Neural Architecture Search

    ...The project includes training scripts, model definitions, and search procedures that show the full workflow from architecture sampling to evaluation. Because ENAS relies on shared weights among candidate models, the implementation emphasizes efficiency and experiment reproducibility.
    Downloads: 0 This Week
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