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- processed/valid/dataset.arrow → Kaludi--data-csgo-weapon-classification/imagefolder-test.parquet +2 -2
- processed/train/dataset.arrow → Kaludi--data-csgo-weapon-classification/imagefolder-train.parquet +2 -2
- raw/image_folders/train/train/AK-47/AK470001.jpg → Kaludi--data-csgo-weapon-classification/imagefolder-validation.parquet +2 -2
- README.md +0 -53
- processed/dataset_dict.json +0 -1
- processed/train/dataset_info.json +0 -35
- processed/train/state.json +0 -17
- processed/valid/dataset_info.json +0 -35
- processed/valid/state.json +0 -17
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processed/valid/dataset.arrow → Kaludi--data-csgo-weapon-classification/imagefolder-test.parquet
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processed/train/dataset.arrow → Kaludi--data-csgo-weapon-classification/imagefolder-train.parquet
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raw/image_folders/train/train/AK-47/AK470001.jpg → Kaludi--data-csgo-weapon-classification/imagefolder-validation.parquet
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README.md
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---
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task_categories:
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- image-classification
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---
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# Dataset for project: csgo-weapon-classification
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## Dataset Description
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This dataset has for project csgo-weapon-classification was collected with the help of a bulk google image downloader.
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### Languages
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The BCP-47 code for the dataset's language is unk.
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## Dataset Structure
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### Data Instances
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A sample from this dataset looks as follows:
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```json
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[
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{
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"image": "<1768x718 RGB PIL image>",
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"target": 0
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},
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{
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"image": "<716x375 RGBA PIL image>",
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"target": 0
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}
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]
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```
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### Dataset Fields
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The dataset has the following fields (also called "features"):
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```json
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{
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"image": "Image(decode=True, id=None)",
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"target": "ClassLabel(names=['AK-47', 'AWP', 'Famas', 'Galil-AR', 'Glock', 'M4A1', 'M4A4', 'P-90', 'SG-553', 'UMP', 'USP'], id=None)"
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}
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```
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### Dataset Splits
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This dataset is split into a train and validation split. The split sizes are as follow:
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| Split name | Num samples |
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| ------------ | ------------------- |
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| train | 1100 |
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| valid | 275 |
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processed/dataset_dict.json
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{"splits": ["train", "valid"]}
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processed/train/dataset_info.json
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{
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"citation": "",
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"description": "AutoTrain generated dataset",
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"features": {
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"image": {
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"_type": "Image"
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},
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"target": {
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"names": [
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"AK-47",
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"AWP",
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"Famas",
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"Galil-AR",
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"Glock",
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"M4A1",
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"M4A4",
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"P-90",
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"SG-553",
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"UMP",
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"USP"
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],
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"_type": "ClassLabel"
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}
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},
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"homepage": "",
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"license": "",
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"splits": {
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"train": {
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"name": "train",
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"num_bytes": 245114734,
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"num_examples": 1100,
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processed/train/state.json
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"_fingerprint": "f08bd56542ad550c",
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"_format_columns": [
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"image",
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processed/valid/dataset_info.json
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{
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"citation": "",
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"description": "AutoTrain generated dataset",
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"target": {
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"names": [
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"AK-47",
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"AWP",
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"Famas",
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"Galil-AR",
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"Glock",
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"M4A1",
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"M4A4",
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"P-90",
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"SG-553",
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"UMP",
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"USP"
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],
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"_type": "ClassLabel"
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"homepage": "",
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"license": "",
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"splits": {
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"name": "valid",
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processed/valid/state.json
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