Commit
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Parent(s):
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commit files to HF hub
Browse files- README.md +2 -2
- config.json +11 -0
- pair_classification.py +29 -0
- pytorch_model.bin +1 -1
- runs/events.out.tfevents.1666962937.sa103.22908.0 +3 -0
README.md
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@@ -11,11 +11,11 @@ model-index:
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results:
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- task:
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name: Image Classification
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type:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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---
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# krenzcolor_chkpt_classifier
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results:
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- task:
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name: Image Classification
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type: pair-classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.3928571343421936
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---
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# krenzcolor_chkpt_classifier
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config.json
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"custom_pipelines": {
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"pair-classification": {
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"impl": "pair_classification.PairClassificationPipeline",
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"pt": [
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"ViTForImageClassification"
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],
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"tf": [
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"TFViTForImageClassification"
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]
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}
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},
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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pair_classification.py
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from torchvision import transforms
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from transformers import ImageClassificationPipeline
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import torch
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class PairClassificationPipeline(ImageClassificationPipeline):
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pipe_to_tensor = transforms.ToTensor()
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pipe_to_pil = transforms.ToPILImage()
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def preprocess(self, image):
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left_image, right_image = self.horizontal_split_image(image)
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model_inputs = self.extract_split_feature(left_image, right_image)
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# model_inputs = super().preprocess(image)
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# print(model_inputs['pixel_values'].shape)
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return model_inputs
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def horizontal_split_image(self, image):
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# image = image.resize((448,224))
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w, h = image.size
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half_w = w//2
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left_image = image.crop([0,0,half_w,h])
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right_image = image.crop([half_w,0,2*half_w,h])
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return left_image, right_image
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def extract_split_feature(self, left_image, right_image):
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model_inputs = self.feature_extractor(images=left_image, return_tensors=self.framework)
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right_inputs = self.feature_extractor(images=right_image, return_tensors=self.framework)
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model_inputs['pixel_values'] = torch.cat([model_inputs['pixel_values'],right_inputs['pixel_values']], dim=1)
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return model_inputs
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 345635761
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version https://git-lfs.github.com/spec/v1
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oid sha256:b5233e44bcfb172d9200f5f0c63a00ac4411a1783bf6dd42b48dce384a468da1
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size 345635761
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runs/events.out.tfevents.1666962937.sa103.22908.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:a878e370777ce85d35b80fa02f4354af89b306a44916d4b592109528e5dad9ed
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size 1939
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