Datasets:

infinite-dataset-hub
/

ProductPicClass

idx int64 0 99	Image_URL stringlengths 9 43	Product_Type stringclasses 10 values	Label stringlengths 4 32
0	https://example.com/images/product1.jpg	Kitchenware	Utensils
1	https://example.com/images/product2.jpg	Electronics	Smartphones
2	https://example.com/images/product3.jpg	Apparel	Footwear
3	https://example.com/images/product4.jpg	Beauty	Makeup
4	https://example.com/images/product5.jpg	Apparel	Clothing
5	https://example.com/images/product6.jpg	Utensils	Knife
6	https://example.com/imag…/smartphone1.jpg	Smartphones	Samsung Galaxy S21
7	https://example.com/images/product6.jpg	Footwear	Sneakers
8	https://example.com/images/product6.jpg	Makeup	Foundation
9	https://example.com/images/product6.jpg	Clothing	Formal_Women_Wear
10	https://example.com/images/product6.jpg	Utensils	Spoon
11	https://example.com/images/product1.jpg	Kitchenware	Utensils
12	https://example.com/images/product6.jpg	Footwear	Sneakers
13	https://example.com/images/product6.jpg	Makeup	Foundation
14	https://example.com/images/product6.jpg	Clothing	Shirts
15	https://example.com/images/product7.jpg	Utensils	Spoon
16	https://example.com/imag…/smartphone2.jpg	Smartphones	iPhone 12
17	https://example.com/images/product7.jpg	Footwear	Boots
18	https://example.com/images/product7.jpg	Makeup	Mascara
19	https://example.com/images/product7.jpg	Clothing	Formal_Men_Wear
20	https://example.com/images/product7.jpg	Utensils	Fork
21	https://example.com/images/product2.jpg	Electronics	Smartphones
22	https://example.com/images/product7.jpg	Footwear	Sandals
23	https://example.com/images/product7.jpg	Makeup	Concealer
24	https://example.com/images/product7.jpg	Clothing	Pants
25	https://example.com/images/product8.jpg	Utensils	Fork
26	https://example.com/imag…/smartphone3.jpg	Smartphones	Google Pixel 5
27	https://example.com/images/product8.jpg	Footwear	Sandals
28	https://example.com/images/product8.jpg	Makeup	Blush
29	https://example.com/images/product8.jpg	Clothing	Casual_Women_Wear
30	https://example.com/images/product8.jpg	Utensils	Knife
31	https://example.com/images/product3.jpg	Apparel	Footwear
32	https://example.com/images/product8.jpg	Footwear	Boots
33	https://example.com/images/product8.jpg	Makeup	Lipstick
34	https://example.com/images/product8.jpg	Clothing	Dresses
35	https://example.com/images/product9.jpg	Utensils	Whisk
36	https://example.com/imag…/smartphone4.jpg	Smartphones	OnePlus 8T
37	https://example.com/images/product9.jpg	Footwear	Loafers
38	https://example.com/images/product9.jpg	Makeup	Eyeliner
39	https://example.com/images/product9.jpg	Clothing	Casual_Men_Wear
40	https://example.com/images/product9.jpg	Utensils	Whisk
41	https://example.com/images/product4.jpg	Beauty	Makeup
42	https://example.com/images/product9.jpg	Footwear	Heels
43	https://example.com/images/product9.jpg	Makeup	Mascara
44	https://example.com/images/product9.jpg	Clothing	Skirts
45	https://example.com/images/product10.jpg	Utensils	Tongs
46	https://example.com/imag…/smartphone5.jpg	Smartphones	Sony Xperia 1 III
47	https://example.com/images/product10.jpg	Footwear	High-tops
48	https://example.com/images/product10.jpg	Makeup	Eyeshadow
49	https://example.com/images/product10.jpg	Clothing	Kids_Wear
50	https://example.com/images/product10.jpg	Utensils	Tongs
51	https://example.com/images/product5.jpg	Apparel	Clothing
52	https://example.com/images/product10.jpg	Footwear	Loafers
53	https://example.com/images/product10.jpg	Makeup	Blush
54	https://example.com/images/product10.jpg	Clothing	Shoes
55	https://example.com/images/product11.jpg	Utensils	Peeler
56	https://example.com/imag…/smartphone6.jpg	Smartphones	Xiaomi Mi 11
57	https://example.com/images/product11.jpg	Footwear	Oxfords
58	https://example.com/images/product11.jpg	Makeup	Lipstick
59	https://example.com/images/product11.jpg	Clothing	Sports_Wear
60	https://example.com/images/product11.jpg	Utensils	Grater
61	https://example.com/images/product6.jpg	Electronics	Smartphones
62	https://example.com/images/product11.jpg	Footwear	Sneakers
63	https://example.com/images/product11.jpg	Makeup	Eyeshadow
64	Image_URL	Product_Type	Label
65	https://example.com/images/product12.jpg	Utensils	Grater
66	https://example.com/imag…/smartphone7.jpg	Smartphones	Apple iPhone SE (2nd generation)
67	https://example.com/images/product12.jpg	Footwear	Ballet Flats
68	https://example.com/images/product12.jpg	Makeup	Lip Liner
69	https://example.com/images/product12.jpg	Clothing	Swimwear
70	https://example.com/images/product12.jpg	Utensils	Spatula
71	https://example.com/images/product7.jpg	Electronics	Smartphones
72	https://example.com/images/product12.jpg	Footwear	Sandals
73	https://example.com/images/product12.jpg	Makeup	Highlighter
74	https://example.com/images/product1.jpg	Kitchenware	Utensils
75	https://example.com/images/product13.jpg	Utensils	Can Opener
76	https://example.com/imag…/smartphone8.jpg	Smartphones	Asus ROG Phone 3
77	https://example.com/images/product13.jpg	Footwear	Cowboy Boots
78	https://example.com/images/product13.jpg	Makeup	Nail Polish
79	https://example.com/images/product13.jpg	Clothing	Fashion_Accessories
80	https://example.com/images/product13.jpg	Utensils	Colander
81	https://example.com/images/product8.jpg	Electronics	Smartphones
82	https://example.com/images/product13.jpg	Footwear	Boots
83	https://example.com/images/product13.jpg	Makeup	Eyeliner
84	https://example.com/images/product2.jpg	Electronics	Smartphones
85	https://example.com/images/product14.jpg	Utensils	Mixing Bowls
86	https://example.com/imag…/smartphone9.jpg	Smartphones	Samsung Galaxy Note 20
87	https://example.com/images/product14.jpg	Footwear	Flip Flops
88	https://example.com/images/product14.jpg	Makeup	Face Mask
89	https://example.com/images/product14.jpg	Clothing	Work_Wear
90	https://example.com/images/product14.jpg	Utensils	Peeler
91	https://example.com/images/product9.jpg	Electronics	Smartphones
92	https://example.com/images/product14.jpg	Footwear	Heels
93	https://example.com/images/product14.jpg	Makeup	False Eyelashes
94	https://example.com/images/product3.jpg	Apparel	Footwear
95	https://example.com/images/product15.jpg	Utensils	Salad Spinner
96	https://example.com/imag…smartphone10.jpg	Smartphones	Huawei P40 Pro
97	https://example.com/images/product15.jpg	Footwear	Running Shoes
98	https://example.com/images/product15.jpg	Makeup	False Eyelashes
99	https://example.com/images/product15.jpg	Clothing	Maternity_Wear

ProductPicClass

tags: product, classification, photography

Note: This is an AI-generated dataset so its content may be inaccurate or false

Dataset Description:

The 'ProductPicClass' dataset comprises various product photography images that have been categorized into classes based on the product type. The dataset is designed to aid machine learning practitioners in developing classification models that can automatically identify and categorize products from images.

Each row in the dataset corresponds to a product photo with an associated class label. The columns include 'Image_ID', 'Image_URL', 'Product_Type', and 'Label'. 'Image_ID' is a unique identifier for each image, 'Image_URL' is the link to the image, 'Product_Type' specifies the type of product shown in the image, and 'Label' denotes the classification assigned to the image.

CSV Content Preview:

Image_ID,Image_URL,Product_Type,Label
1,https://example.com/images/product1.jpg,Kitchenware,Utensils
2,https://example.com/images/product2.jpg,Electronics,Smartphones
3,https://example.com/images/product3.jpg,Apparel,Footwear
4,https://example.com/images/product4.jpg,Beauty,Makeup
5,https://example.com/images/product5.jpg,Apparel,Clothing

In this preview, the dataset includes five entries. Each entry has a unique identifier, a URL to the corresponding product photo, the type of product depicted in the image, and a label that classifies the image according to its content. For instance, the first entry has an image of kitchenware utensils, while the second features a smartphone, and so on.

Source of the data:

The dataset was generated using the Infinite Dataset Hub and microsoft/Phi-3-mini-4k-instruct using the query 'product photography':

Dataset Generation Page: https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub?q=product+photography&dataset=ProductPicClass&tags=product,+classification,+photography
Model: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct
More Datasets: https://huggingface.co/datasets?other=infinite-dataset-hub

Downloads last month: 36

Edit dataset card

Size of downloaded dataset files:

6.31 kB

Size of the auto-converted Parquet files:

4.16 kB

Number of rows:

100

Data Sourcing report

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No elements in this dataset have been identified as either opted-out, or opted-in, by their creator.