fixed dataset with original images

README.md

@@ -1,19 +1,4 @@
 ---
-license: apache-2.0
-task_categories:
-  - image-classification
-  - text-classification
-  - zero-shot-classification
-tags:
-  - e-commerce
-  - product-categorization
-  - taxonomy
-  - multimodal
-  - shopify
-  - retail
-  - product-catalog
-size_categories:
-  - 10K<n<100K
 dataset_info:
   features:
   - name: product_title
@@ -32,13 +17,13 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 7425492387
-    num_examples: 38631
+    num_bytes: 2091545165
+    num_examples: 38917
   - name: test
-    num_bytes: 2085920280
-    num_examples: 9658
-  download_size: 9496974081
-  dataset_size: 9511412667
+    num_bytes: 512186339
+    num_examples: 9730
+  download_size: 2469913869
+  dataset_size: 2603731504
 configs:
 - config_name: default
   data_files:
@@ -47,127 +32,3 @@ configs:
   - split: test
     path: data/test-*
 ---
-
-# The Catalogue: Product Taxonomy Classification Benchmark
-
-A large-scale, multimodal benchmark dataset for product taxonomy classification, featuring real e-commerce products with images, descriptions, and hierarchical category labels.
-
-## Dataset Description
-
-**The Catalogue** is a benchmark dataset designed to evaluate AI models on the task of classifying products into a standardized taxonomy. Each sample includes a product image, title, description, brand, and the ground-truth category from Shopify's product taxonomy.
-
-This dataset is ideal for:
-- Evaluating vision-language models on real-world product classification
-- Benchmarking multimodal understanding in e-commerce contexts
-- Testing hierarchical classification capabilities
-- Comparing different approaches to product categorization
-
-### Dataset Statistics
-
-| Metric | Value |
-|--------|-------|
-| Total samples | 48,289 |
-| Unique categories | 10,476 |
-| Unique brands | 28,913 |
-| Products with descriptions | 92.9% |
-| Products with brand | 98.2% |
-| Average category depth | 4.5 levels |
-| Category depth range | 1-8 levels |
-
-### Top-Level Category Distribution
-
-| Category | Count | Percentage |
-|----------|-------|------------|
-| Home & Garden | 7,912 | 16.4% |
-| Sporting Goods | 6,968 | 14.4% |
-| Arts & Entertainment | 5,558 | 11.5% |
-| Hardware | 5,137 | 10.6% |
-| Vehicles & Parts | 2,555 | 5.3% |
-| Business & Industrial | 2,435 | 5.0% |
-| Electronics | 2,344 | 4.9% |
-| Apparel & Accessories | 2,173 | 4.5% |
-| Health & Beauty | 2,162 | 4.5% |
-| Food, Beverages & Tobacco | 2,036 | 4.2% |
-| Animals & Pet Supplies | 1,922 | 4.0% |
-| Furniture | 1,707 | 3.5% |
-| Baby & Toddler | 1,226 | 2.5% |
-| Toys & Games | 1,153 | 2.4% |
-| Office Supplies | 1,129 | 2.3% |
-| Cameras & Optics | 967 | 2.0% |
-| Other | 900 | 1.9% |
-
-## Dataset Structure
-
-### Data Fields
-
-| Field | Type | Description |
-|-------|------|-------------|
-| `product_title` | string | Product title |
-| `product_description` | string | Product description (may be empty) |
-| `product_image` | Image | Product image |
-| `potential_product_categories` | list[string] | Candidate category paths |
-| `ground_truth_brand` | string | Brand name (may be empty) |
-| `ground_truth_is_secondhand` | boolean | Whether the product is secondhand |
-| `ground_truth_category` | string | Ground truth category path |
-
-### Category Format
-
-Categories follow a hierarchical path format:
-```
-Electronics > Computers > Laptops
-Home & Garden > Kitchen & Dining > Cookware
-```
-
-### Data Splits
-
-| Split | Samples | Percentage |
-|-------|---------|------------|
-| Train | 38,631 | 80% |
-| Test | 9,658 | 20% |
-
-## Usage
-
-```python
-from datasets import load_dataset
-
-dataset = load_dataset("Shopify/product-catalogue")
-
-# Access splits
-train_data = dataset["train"]
-test_data = dataset["test"]
-
-# Example
-sample = train_data[0]
-print(f"Title: {sample['product_title']}")
-print(f"Category: {sample['ground_truth_category']}")
-sample['product_image'].show()
-```
-
-## Evaluation
-
-The primary task is to predict the `ground_truth_category` given the product's image, title, and optionally description/brand.
-
-Suggested metrics:
-- Hierarchical F1 for categories
-- Precision and recall for brand and is_secondhand
-
-## Source
-
-Products were sampled from Shopify's merchant catalog, representing real e-commerce products across diverse categories and industries.
-
-## License
-
-Apache 2.0
-
-## Citation
-
-```bibtex
-@dataset{product-catalogue,
-  title={The Catalogue: Product Taxonomy Classification Benchmark},
-  author={Shopify},
-  year={2025},
-  publisher={Hugging Face},
-  url={https://huggingface.co/datasets/Shopify/the-catalogue-public-beta}
-}
-```
-

data/{test-00000-of-00005.parquet → test-00000-of-00002.parquet}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7ed14e760d9d879a3fc25aec0466997e068dea3a03fb6db5dc8e85fbad9c7d32
-size 421327327
+oid sha256:7bf632d0158145577a0961866d84113d80408e18094ad7afaebaae77804620cc
+size 249241197

data/{test-00001-of-00005.parquet → test-00001-of-00002.parquet}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cacdcfcbf608dbe873cb542b7222038a2c0aae86f0016beba3b5fb7d36932141
-size 383746612
+oid sha256:ceedd89201855bc0d89490ea01cdd43c81b33552712e7f271e43875660e9db93
+size 247200812

data/test-00004-of-00005.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f638327f84ad749dee73a7ad867ddf9146c877c2a81119e5bd77f2770351ffdf
-size 354477773

data/{test-00002-of-00005.parquet → train-00000-of-00005.parquet}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9a46ffd4a6dafa8f2bfc03ded46da5d65cedaed0d41f70523f84f3b3a166086e
-size 377646277
+oid sha256:d91640b0ffdfbef90bb0da4c2c216bbf798c939b04d13b27e76c8a043f2b2f01
+size 399284005

data/train-00000-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6ecb8da7f551ef0fbda305f6352ce4e96ac43f1c02d26bbf4870a52d6f458f88
-size 503726506

data/{test-00003-of-00005.parquet → train-00001-of-00005.parquet}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9bbd69012d2a586daf4917cc600282515de9e1cecc1bd8462c50da73347bb2c0
-size 380444166
+oid sha256:842dcd2ee9ca39c3c1a84a807e1c035af4be14cda5e0ba31f9ee7c1c6c9f7bad
+size 392510433

data/train-00001-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3269d7159c99e6b9fc8d76ef8bea8582b1d58a142de298dcceae3a60c66fdce9
-size 520278040

data/train-00002-of-00005.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:082cf8b440075b9ed7623526cfa06f1e38aefc7151f5955465fbb6c736780205
+size 396746227

data/train-00002-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e97aa615f8fddf6ac62bf1c3324f87b5870976cb8d0877965203c6587ebacd3a
-size 515239613

data/train-00003-of-00005.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:16f2199171197adcb46324e78fcfb4f1c59f69f8236c934a7c3b5d04bf81abda
+size 393166550

data/train-00003-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f9528c96850c2ead086079b9ae45fefcd25959ef6a0ef63e0f3bbceb634d3f91
-size 497497890

data/train-00004-of-00005.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c590bf45e1cc89ba63f39a8a35a7cf67383df4accadd873ca1f3c759cb9fa74
+size 391764645

data/train-00004-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:40cf0825f7e360c9ce0cb003d6877b6e2b6356b6a4b850abf768abc601cd18ef
-size 515621914

data/train-00005-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:d2b7917ab4ff829c8e85865deaeb543b81e24b0677f4a545328cb13d760186f0
-size 490269450

data/train-00006-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:168673f56658ec6b00c8a46eb2fad3d8232316ffa4e373904ce3e90bb9363d79
-size 547480337

data/train-00007-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:4581750598636dbc7f100aa0a2842ab5107913e48b6a329fcfd14483b978dc33
-size 478866637

data/train-00008-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:1489d1ae712b8fcb039b3eba998caec6f839414d3b188b49a6a5c3ca696cf151
-size 505629872

data/train-00009-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a106666138311260ec7ab226931b6a564098f905e3b474043bc11b308b005aa7
-size 484171932

data/train-00010-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:72537642ebf2c5121c08ae643817559c11934e0434cb9c0f1663284bd615419b
-size 521487950

data/train-00011-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9307d2c68872ea63022b83466664567c49dbf86d443977339461f8d51096d83f
-size 514457271

data/train-00012-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:477f1b00e7cccb13c90019dad41148735dc93b9e1f3e7e6027a4a0dcc37dfe40
-size 508913925

data/train-00013-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cffd7398de2ee8568139da4857f3278bdf114e374bed8bf7e86fb56211847f49
-size 477681393

data/train-00014-of-00015.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6b699ef6f1dad92883ff366728af91d0b40ebdaf508d3f0c0aefd8cf257336a0
-size 498009196