Image Classification
Transformers
PyTorch
Core ML
ONNX
Safetensors
convnext
Generated from Trainer
Eval Results (legacy)
Instructions to use flyswot/convnext-tiny-224_flyswot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flyswot/convnext-tiny-224_flyswot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="flyswot/convnext-tiny-224_flyswot") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("flyswot/convnext-tiny-224_flyswot") model = AutoModelForImageClassification.from_pretrained("flyswot/convnext-tiny-224_flyswot") - Notebooks
- Google Colab
- Kaggle
Upload processor
#4
by davanstrien HF Staff - opened
- preprocessor_config.json +6 -1
preprocessor_config.json
CHANGED
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@@ -1,6 +1,7 @@
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{
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"crop_pct": 0.875,
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "ConvNextFeatureExtractor",
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"image_mean": [
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@@ -8,11 +9,15 @@
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0.456,
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0.406
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],
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"resample": 3,
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-
"
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}
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{
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"crop_pct": 0.875,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"feature_extractor_type": "ConvNextFeatureExtractor",
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"image_mean": [
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0.456,
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0.406
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],
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"image_processor_type": "ConvNextImageProcessor",
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"resample": 3,
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+
"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 224
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}
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}
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