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Upload processor

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  1. README.md +4 -5
  2. preprocessor_config.json +14 -0
README.md CHANGED
@@ -1,11 +1,6 @@
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  ---
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  license: mit
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  library_name: transformers
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- widget:
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- - src: >-
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- https://fema-cap-imagery.s3.amazonaws.com/Images/CAP_-_Flooding_Spring_2023/Source/IAWG_23-B-5061/A0005/D75_0793_DxO_PL6_P.jpg
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- - example_title: Example classification of flooded scene
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- pipeline_tag: image-classification
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  tags:
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  - LADI
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  - Aerial Imagery
@@ -13,6 +8,10 @@ tags:
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  - Emergency Management
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  datasets:
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  - MITLL/LADI-v2-dataset
 
 
 
 
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  ---
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  # Model Card for MITLL/LADI-v2-classifier-large-reference
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  LADI-v2-classifier-large-reference is based on [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) and fine-tuned on the [MITLL/LADI-v2-dataset](https://huggingface.co/datasets/MITLL/LADI-v2-dataset). LADI-v2-classifier is trained to identify labels of interest to disaster response managers from aerial images.
 
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  ---
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  license: mit
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  library_name: transformers
 
 
 
 
 
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  tags:
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  - LADI
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  - Aerial Imagery
 
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  - Emergency Management
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  datasets:
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  - MITLL/LADI-v2-dataset
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+ widget:
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+ - src: https://fema-cap-imagery.s3.amazonaws.com/Images/CAP_-_Flooding_Spring_2023/Source/IAWG_23-B-5061/A0005/D75_0793_DxO_PL6_P.jpg
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+ - example_title: Example classification of flooded scene
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+ pipeline_tag: image-classification
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  ---
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  # Model Card for MITLL/LADI-v2-classifier-large-reference
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  LADI-v2-classifier-large-reference is based on [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) and fine-tuned on the [MITLL/LADI-v2-dataset](https://huggingface.co/datasets/MITLL/LADI-v2-dataset). LADI-v2-classifier is trained to identify labels of interest to disaster response managers from aerial images.
preprocessor_config.json CHANGED
@@ -1,4 +1,18 @@
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  {
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  {
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+ "_valid_processor_keys": [
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+ "images",
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+ "do_resize",
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+ "size",
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+ "resample",
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+ "do_rescale",
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+ "rescale_factor",
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+ "do_normalize",
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+ "image_mean",
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+ "image_std",
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+ "return_tensors",
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+ "data_format",
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+ "input_data_format"
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+ ],
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  "do_normalize": true,
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  "do_rescale": true,
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  "do_resize": true,