commit files to HF hub
Browse files- README.md +52 -0
- config.json +36 -0
- images/bathroom.jpg +0 -0
- images/bedroom.jpg +0 -0
- images/dining_room.jpg +0 -0
- images/kitchen.jpg +0 -0
- images/living_room.jpg +0 -0
- preprocessor_config.json +17 -0
- pytorch_model.bin +3 -0
- runs/events.out.tfevents.1644646376.abd485e46fe5.81.0 +3 -0
README.md
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---
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tags:
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- image-classification
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- pytorch
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- huggingpics
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metrics:
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- accuracy
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model-index:
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- name: household-rooms
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results:
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- task:
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name: Image Classification
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type: image-classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8482142686843872
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---
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# household-rooms
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Autogenerated by HuggingPics🤗🖼️
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Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
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Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
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## Example Images
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#### bathroom
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![bathroom](images/bathroom.jpg)
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#### bedroom
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![bedroom](images/bedroom.jpg)
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#### dining room
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![dining room](images/dining_room.jpg)
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#### kitchen
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![kitchen](images/kitchen.jpg)
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#### living room
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![living room](images/living_room.jpg)
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config.json
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{
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"_name_or_path": "google/vit-base-patch16-224-in21k",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "bathroom",
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"1": "bedroom",
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"2": "dining room",
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"3": "kitchen",
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"4": "living room"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"bathroom": "0",
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"bedroom": "1",
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"dining room": "2",
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"kitchen": "3",
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"living room": "4"
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.16.2"
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}
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images/bathroom.jpg
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images/bedroom.jpg
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images/dining_room.jpg
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images/kitchen.jpg
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images/living_room.jpg
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "ViTFeatureExtractor",
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"resample": 2,
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"size": 224
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}
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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:dfc7eb260068b41bcf5ae58b2f7fe72185e0735c75d42cd74a2d8abde7a1744b
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size 343286257
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runs/events.out.tfevents.1644646376.abd485e46fe5.81.0
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:2146806f8dfe435c02f8b4225f249d5a85593f00d8c9dcb312a4d263c7e21f56
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size 1444
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