deepghs / ccip_onnx

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zero-shot-image-classification

Introduction of ccip_onnx

Model Details of ccip_onnx

Model F1 Score Precision Recall Threshold Cluster_2 Cluster_Free
ccip-caformer_b36-24 0.940925 0.938254 0.943612 0.213231 0.89508 0.957017
ccip-caformer-24-randaug-pruned 0.917211 0.933481 0.901499 0.178475 0.890366 0.922375
ccip-v2-caformer_s36-10 0.906422 0.932779 0.881513 0.207757 0.874592 0.89241
ccip-caformer-6-randaug-pruned_fp32 0.878403 0.893648 0.863669 0.195122 0.810176 0.897904
ccip-caformer-5_fp32 0.864363 0.90155 0.830121 0.183973 0.792051 0.862289
ccip-caformer-4_fp32 0.844967 0.870553 0.820842 0.18367 0.795565 0.868133
ccip-caformer_query-12 0.823928 0.871122 0.781585 0.141308 0.787237 0.809426
ccip-caformer-23_randaug_fp32 0.81625 0.854134 0.781585 0.136797 0.745697 0.8068
ccip-caformer-2-randaug-pruned_fp32 0.78561 0.800148 0.771592 0.171053 0.686617 0.728195
ccip-caformer-2_fp32 0.755125 0.790172 0.723055 0.141275 0.64977 0.718516
  • The calculation of F1 Score , Precision , and Recall considers "the characters in both images are the same" as a positive case. Threshold is determined by finding the maximum value on the F1 Score curve.
  • Cluster_2 represents the approximate optimal clustering solution obtained by tuning the eps value in DBSCAN clustering algorithm with min_samples set to 2 , and evaluating the similarity between the obtained clusters and the true distribution using the random_adjust_score .
  • Cluster_Free represents the approximate optimal solution obtained by tuning the max_eps and min_samples values in the OPTICS clustering algorithm, and evaluating the similarity between the obtained clusters and the true distribution using the random_adjust_score .

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More Information About ccip_onnx huggingface.co Model

More ccip_onnx license Visit here:

https://choosealicense.com/licenses/openrail

ccip_onnx huggingface.co

ccip_onnx huggingface.co is an AI model on huggingface.co that provides ccip_onnx's model effect (), which can be used instantly with this deepghs ccip_onnx model. huggingface.co supports a free trial of the ccip_onnx model, and also provides paid use of the ccip_onnx. Support call ccip_onnx model through api, including Node.js, Python, http.

ccip_onnx huggingface.co Url

https://huggingface.co/deepghs/ccip_onnx

deepghs ccip_onnx online free

ccip_onnx huggingface.co is an online trial and call api platform, which integrates ccip_onnx's modeling effects, including api services, and provides a free online trial of ccip_onnx, you can try ccip_onnx online for free by clicking the link below.

deepghs ccip_onnx online free url in huggingface.co:

https://huggingface.co/deepghs/ccip_onnx

ccip_onnx install

ccip_onnx is an open source model from GitHub that offers a free installation service, and any user can find ccip_onnx on GitHub to install. At the same time, huggingface.co provides the effect of ccip_onnx install, users can directly use ccip_onnx installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

ccip_onnx install url in huggingface.co:

https://huggingface.co/deepghs/ccip_onnx

Url of ccip_onnx

ccip_onnx huggingface.co Url

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