mobilenet-v2-1.0-224 is one of MobileNet* models, which are small, low-latency, low-power, and parameterized to meet the resource constraints of a variety of use cases. They can be used for classification, detection, embeddings, and segmentation like other popular large-scale models. For details, see the paper.
input , shape: [1x224x224x3], format: [BxHxWxC], where:
- B - batch size - H - image height - W - image width - C - number of channels
Expected color order: RGB. Mean values: [127.5, 127.5, 127.5], scale factor for each channel: 127.5.
input, shape: [1x3x224x224], format: [BxCxHxW], where:
- B - batch size - C - number of channels - H - image height - W - image width
Expected color order: BGR.
MobilenetV2/Predictions/Reshape_1. Probabilities for all dataset classes (0 class is background). Probabilities are represented in logits format.
MobilenetV2/Predictions/Softmax. Probabilities for all dataset classes (0 class is background). Probabilities are represented in logits format. Shape: [1,1001], format: [BxC], where:
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