Datasets:

BowerApp
/

bower-waste-annotations

image_id stringlengths 13 19	image_height int32 205 901	image_width int32 256 901	material stringclasses 13 values	object stringclasses 19 values	x1 float64 0 807	y1 float64 0 793	x2 float64 37 901	y2 float64 19 901
3858098582085160810	750	900	Electronic Waste	E-cigarette	199	406	648	487
473219887982654032	900	900	Plastic - Hard	Cosmetics Containers	368	0	500	731
213318524120860226	900	900	Textiles	null	245	301	685	673
461249427308373244	900	900	Composite	null	98	321	672	495
300921795038673201	901	901	Plastic - Hard	null	501	557	854	800
444595037337258601	900	900	Plastic - Hard	Cosmetics Containers	176	228	702	598
462267878504307452	900	900	Electronic Waste	Electronic Device	159	195	738	664
69074512280145267	750	900	Textiles	null	173	213	704	544
92928459398084098	900	900	Plastic - Hard	Cosmetics Containers	328	150	534	639
109049060613648495	900	900	Electronic Waste	Electronic Device	2	505	212	847
539461615746297271	900	900	Plastic - Hard	Cosmetics Containers	61	292	815	598
5560351064886885544	750	900	Electronic Waste	E-cigarette	296	290	698	351
188223416630048547	900	900	Plastic - Hard	Cosmetics Containers	31	51	853	863
49721414192797011	678	900	Textiles	null	0	138	898	544
176795349676602075	900	900	null	null	0	0	900	900
159538481545643603	750	900	Plastic - Hard	Jar	79	140	756	567
981570476354414063	900	900	Plastic - Hard	Jar	252	360	612	708
8664883855552330036	900	900	Plastic - Hard	Jar	223	196	658	754
921467648670971247	900	900	Glass - Non-coloured	Jar	60	0	810	798
408628691355518609	900	900	Glass - Non-coloured	Jar	205	116	685	788
444368644293814822	900	900	Glass - Non-coloured	Jar	287	140	592	775
935421734127977152	900	900	Glass - Non-coloured	Jar	120	0	696	756
303159708941440307	900	900	Plastic - Hard	Jar	236	165	584	682
997440199807557313	900	900	Glass - Non-coloured	Jar	222	60	654	642
1799157912258356538	582	901	Glass - Non-coloured	Jar	222.246667	103.0625	666.74	472.875
1243787205284654426	901	901	Glass - Coloured	Jar	60.066667	0	876.973333	901
9221971301955964171	900	900	Plastic - Hard	Jar	252	168	654	738
8394959831839564495	519	901	Plastic - Hard	Jar	244.536255	158.847565	637.384644	362.531952
928206148584561833	900	900	Plastic - Hard	Jar	300	192	570	732
929949369517317425	364	364	Plastic - Hard	Jar	72.8	65.52	259.653333	303.333333
9218632165455135895	900	900	Plastic - Hard	Jar	150	240	696	624
5318808081775426932	900	900	Glass - Coloured	Jar	108	30	786	828
9043214678446969434	900	900	Plastic - Hard	Jar	273.563995	193.737473	584.939819	674.969421
494026304959832857	900	900	Glass - Non-coloured	Jar	693	393	882	788
4987765277535112818	582	901	Glass - Coloured	Jar	222.246667	145.5	690.766667	412.25
952489440243990587	900	900	Plastic - Hard	Jar	264	126	678	624
992857408002332044	900	900	Glass - Non-coloured	Jar	138	0	684	720
199062423147498494	570	900	Glass - Non-coloured	Jar	232	152	653	381
494026304959832857	900	900	Glass - Non-coloured	Jar	267	75	690	854
983413437474156664	900	900	Plastic - Hard	Jar	318	258	810	768
235390642069833205	900	900	Glass - Non-coloured	Jar	232	0	688	714
975144205800078173	364	364	Plastic - Hard	Jar	111.626667	46.106667	254.8	322.746667
1617997196063182094	900	900	Glass - Coloured	Jar	204	96	702	708
139931078227206012	900	900	Plastic - Hard	Jar	3	2	884	900
168111870068755764	900	900	Glass - Non-coloured	Jar	170	2	722	842
9212455128184174144	574	900	Plastic - Hard	Jar	228	151.052632	672	435.031579
92235794617840521	900	900	Glass - Non-coloured	Jar	0	414	160	651
2033065305718869992	900	900	Glass - Coloured	Jar	312	0	690	696
11363715435989907	900	900	Glass - Non-coloured	Jar	206	310	672	785
333284036031753956	901	901	Glass - Non-coloured	Jar	230	125	704	739
964128303090077874	900	900	Glass - Non-coloured	Jar	216	0	684	762
280428599250896915	900	900	Glass - Non-coloured	Jar	106	1	758	867
5504238865671564768	519	901	Glass - Coloured	Jar	210.233333	144.837209	648.72	380.197674
973155710155952531	900	900	Plastic - Hard	Jar	264	156	594	702
464995280433788061	900	900	Glass - Non-coloured	Jar	248	74	700	846
429931303318245117	900	900	Glass - Non-coloured	Jar	211	0	707	683
947906010317237909	900	900	Plastic - Hard	Jar	132	30	714	804
23291029448140423	900	900	Glass - Non-coloured	Jar	287	445	610	643
931123424304328351	900	900	Glass - Non-coloured	Jar	204	48	702	810
40265696509677273	900	900	Plastic - Hard	Jar	149	38	692	569
4349358874325663336	364	364	Glass - Coloured	Jar	113	81	274	268
925117432784596556	900	900	Glass - Non-coloured	Jar	102	42	768	900
1542062707689295255	900	900	Glass - Coloured	Jar	264	72	654	792
964450378923487686	900	900	Glass - Non-coloured	Jar	312	162	588	660
1320521459795842201	900	900	Glass - Non-coloured	Jar	246	114	612	660
192857578756810150	900	900	Glass - Non-coloured	Jar	710	0	900	452
323637641905614896	900	900	Plastic - Hard	Jar	221	167	692	895
8348953322034888465	901	901	Plastic - Hard	Jar	267.317047	2.076019	650.483276	714.955566
9219029335448198223	901	901	Glass - Non-coloured	Jar	120.133333	24.026667	720.8	834.926667
134662899090372875	900	900	Plastic - Hard	Jar	299	207	628	900
340756877187047129	900	900	Glass - Non-coloured	Jar	226	151	628	711
938572119441443548	900	900	Plastic - Hard	Jar	282	174	678	744
965760159607276252	901	901	Glass - Non-coloured	Jar	198.22	72.08	744.826667	846.94
215112012575419846	900	900	Glass - Non-coloured	Jar	260	62	592	833
459461490523946943	900	900	Glass - Non-coloured	Jar	204	79	622	758
986764361221506379	900	900	Glass - Non-coloured	Jar	240	60	720	774
4180740689578460345	585	900	Glass - Coloured	Jar	246	144.742268	618	458.350515
6762186929819965433	900	900	Plastic - Hard	Jar	0	0	900	681
1700460956580957136	519	901	Glass - Non-coloured	Jar	258.286667	138.802326	672.746667	362.093023
959715198517758668	900	900	Plastic - Hard	Jar	132	174	624	654
993226100122218653	900	900	Plastic - Hard	Jar	186	174	726	738
320073709870805489	900	900	Plastic - Hard	Jar	173	79	782	798
134678659123475584	901	901	Plastic - Hard	Jar	54	0	831	901
173107773641923838	900	900	Glass - Coloured	Jar	277	120	645	817
9218218723035784878	900	900	Glass - Non-coloured	Jar	216	0	702	870
972457088590412768	900	900	Glass - Non-coloured	Jar	288	168	804	780
943057920790465529	900	900	Glass - Non-coloured	Jar	246	114	582	786
978754606254757773	900	900	Glass - Non-coloured	Jar	216	0	630	762
982268473847064108	900	900	Glass - Non-coloured	Jar	204	66	660	894
946804692292601118	900	900	Plastic - Hard	Jar	306	174	654	594
3512469015084608428	628	900	Glass - Coloured	Jar	204	187.192308	690	458.923077
936657968562168556	574	900	Plastic - Hard	Jar	300	126.884211	606	398.778947
4069169106292785964	900	900	Glass - Non-coloured	Jar	17	111	158	356
505019756233452808	900	900	Plastic - Hard	Jar	137	128	719	715
445104104061076511	901	901	Glass - Non-coloured	Jar	249	3	766	894
967417204170439821	900	900	Plastic - Hard	Jar	216	300	642	588
2392312373494115769	570	900	Glass - Coloured	Jar	216	144	588	426
426714371653399553	900	900	Plastic - Hard	Jar	0	81	221	407
926433926665656080	900	900	Glass - Coloured	Jar	324	114	624	810
2194320707471639805	900	900	Glass - Coloured	Jar	252	138	642	726

End of preview. Expand in Data Studio

Dataset Card for waste annotations made by the recycling solution Bower

The data offered by Bower (Sugi Group AB) in collaboration with Google.org

Dataset Summary

The bower-waste-annotations dataset consists of 1440 images of waste and various consumer items taken by consumer phone cameras. The images are annotated with Material type and Object type classes, listed below. The images and annotations has been manually reviewed to ensure correctness. It is assumed to have high quality of both bounding box accuracy and material + object combination. The purpose of the dataset has been to validate models - therefor all images in this set is categorized as validation data. As quality of annotations is high, one can use this as ground truth for validating models. This data set was created in a collaboration with Google.org and Google employees as part of the Google Impact Challenge: Tech for social good support that Bower got H1 2024. Which had as goal to create impact in the area of sustainability and waste. Any use of this data that contributes to this purpose is highly appreciated! Let us know how you contribute.

Number of Images

{'valid': 1440}

Taxonomy and description

Object type

Object Type	Description
`Aerosol`	A gas-tight, pressure-resistant container with a valve and propellant. When the valve is opened, the propellant forces the product from the container in a fine or coarse spray pattern or stream. Example: spray cans for paint, furniture polish, etc., under pressure. Excludes atomizers, as they do not rely on a pressurized container to propel product.
`Battery`
`Blister pack`	A type of packaging in which the item is secured between a preformed (usually transparent plastic) dome or "bubble" and a paperboard surface or "carrier." Attachment may be by stapling, heat-sealing, gluing, or other means. Often thermoformed from polyvinyl chloride, although other thermoplastics can be used.
`Book`
`Bottle`	A container with a round neck of relatively smaller diameter than the body, capable of holding a closure for retention of contents. It may be round, oval, square, oblong, or a combination, and is generally made of glass or plastic. Bottles can be disposable, recyclable, returnable, or reusable.
`Box/Card/Tray/Crate`	A non-specific term for a rigid, three-dimensional container with closed or semi-closed faces. Boxes and crates are made from various materials and may be used for storage or display. Trays are shallow containers used for display. Includes open-ended non-rigid containers like sleeves.
`Gable Top`	Package for liquids shaped like a gable top (triangle top), usually made of cardboard.
`Aseptic Flat Top Carton`	A rectangular-shaped, stackable package designed for liquids like juice or milk, made of multilayer laminated materials (e.g., Tetra Pak).
`Tube`	A cylindrical container sealed on one end, closed with a cap or dispenser on the other (e.g., toothpaste tube).
`E-cigarette`
`Bulb`
`Can/Tin/Cylinder`	Metallic, generally cylindrical containers of unspecified size, used for various items. Cylinders have rigid, straight sides with circular ends of equal size.
`Cosmetics containers`	Containers for makeup products like eyelashes, eyeliner, lipsticks, etc.
`Cup/Tub/Bowl/Bucket`	Flat-bottomed containers with a base of any shape, usually used for foods like ice cream, margarine, yogurt, and sour cream. They may or may not have lids and are typically made of paper, plastic, or other materials.
`Jar`	Rigid container made of glass, stone, plastic, or other material, with a large opening for storing products such as jams and honey.
`Electronic device`
`Wrapper/Foil/Net/Bag/Flexibles`	Flexible containers and materials used to enclose all or part of an item. Includes wrappers, gas-tight packs, nets for holding items, and bags or other flexible containers that may be sealed.
`Jug`	Cylindrical container with a handle, lid, or spout, used for holding and pouring liquids.
`Lid/Cap`
`Other medical containers/Pharmaceuticals`	Example: Nasal spray containers
`Paper product`	Includes white paper, newspaper, magazines, and other paper-based items.
`Other`

Material type

Material Type	Description
`Hard plastic`	Rigid plastics that maintain their shape, such as bottles, containers, toys, and household items made from materials like PET or HDPE.
`Soft plastic`	Flexible plastics that can be easily bent or scrunched, including plastic bags, wrappers, and films made from materials like LDPE.
`Other plastic`	Plastics that don't fit into hard or soft categories, possibly including bioplastics, mixed polymers, or specialized plastic products.
`Fiber - Paper`	Thin sheets made from pressed fibers, used for writing, printing, and packaging, such as office paper and newspapers.
`Fiber - Cardboard / Paper Packaging`	Thicker paper materials used for packaging, like corrugated cardboard boxes, paperboard cartons, and other sturdy paper packaging.
`Fiber - Other`	Other fiber-based materials not classified as standard paper or cardboard, such as insulation or specialized industrial fibers.
`Metal`	Materials made from metals like aluminum, steel, copper, and other metal alloys, used in cans, appliances, and construction materials.
`Glass - Coloured`	Glass materials that are tinted or colored, such as green or brown bottles and decorative stained glass items.
`Glass - Non-coloured`	Clear or transparent glass materials like window panes, clear bottles, and jars without any coloration.
`Composite`	Materials made from two or more different substances that remain distinct, such as Tetra Pak cartons combining paperboard, plastic, and aluminum.
`Hazardous waste`	Waste materials that are dangerous or potentially harmful to human health or the environment, like chemicals, batteries, and pesticides.
`Electronic waste`	Discarded electronic devices and components, including computers, smartphones, televisions, and electronic accessories.
`Organic waste`	Biodegradable waste derived from living organisms, such as food scraps, yard waste, and agricultural waste.
`Textiles`	Fabrics and cloth materials made from natural or synthetic fibers, used in clothing, upholstery, and linens.
`Wood`	Material derived from trees, including lumber, plywood, and wooden products used in construction and furniture.
`Rubber & Leather`	Materials made from natural or synthetic rubber (like tires) and animal hides (leather goods such as shoes and belts).
`Other`	Materials that do not fit into any of the specified categories above, including unique or miscellaneous items.

Languages

English

Data Instances

A sample from the validation set is provided below:

{
  ...
}

Data Splits

Validation dataset only

Dataset Creation

Images collected from consumer phone cameras and annotated manually

Annotations

Annotation process

Pre-labelling using Grounding-DINO model (bounding boxes and labels)
Manual annotation using LabelBox
Review by Taxonomy expert for ensured quality

Considerations for Using the Data

Appreciate creditaion of Bower (Sugi Group AB) from usage of the data

Social Impact of Dataset

This dataset was created in a collaboration with Google.org and Google employees as part of the Google Impact Challenge: Tech for social good support that Bower got H1 2024. Goal with the project was to increase recycling rates throughout the world - this by incorporating Computer vision solutions in to the Bower-app to enable users to scan any type of trash and get correct sorting guidance on these items. Which had as goal to create impact in the area of sustainability and waste. Any use of this data that contributes to this purpose is highly appreciated! Let us know how you contribute.

Discussion of Biases

Other Known Limitations

Additional Information

Contributors

Lucas Nilsson, Linda Attby, Louise Rönne, Henrik Erskérs, Jeremy, Suhani

Licensing Information

This work is licensed under a MIT license

Contributions

Thanks to Google.org for making this possible, as well as the Google Fellows joining Bower for 6 months to enable this (Jeremy, Vicent, Suhani, Vivek, Ole and Rita).

Downloads last month: 108

Size of downloaded dataset files:

225 MB

Size of the auto-converted Parquet files:

225 MB

Number of rows:

2,546