We introduce a large-scale image dataset EasyPortrait for portrait segmentation and face parsing. Proposed dataset can be used in several tasks, such as background removal in conference applications, teeth whitening, face skin enhancement, red eye removal or eye colorization, and so on.
EasyPortrait dataset size is about 26GB, and it contains 20 000 RGB images with high quality annotated masks. This dataset is divided into training set, validation set and test set by hashed subject user_id. The training set includes 14000 images, the validation set includes 2000 images, and the test set includes 4000 images.
Training images were received from 5,947 unique users, while validation was from 860 and testing was from 1,570. On average, each EasyPortrait image has 254 polygon points, from which it can be concluded that the annotation is of high quality. Segmentation masks were created from polygons for each annotation.
Annotations are presented as 2D-arrays, images in *.png format with several classes:
Index | Class |
---|---|
0 | BACKGROUND |
1 | PERSON |
2 | SKIN |
3 | LEFT BROW |
4 | RIGHT_BROW |
5 | LEFT_EYE |
6 | RIGHT_EYE |
7 | LIPS |
8 | TEETH |
Also, we provide some additional meta-information for dataset in annotations/meta.zip file:
attachment_id | user_id | data_hash | width | height | brightness | train | test | valid | |
---|---|---|---|---|---|---|---|---|---|
0 | de81cc1c-... | 1b... | e8f... | 1440 | 1920 | 136 | True | False | False |
1 | 3c0cec5a-... | 64... | df5... | 1440 | 1920 | 148 | False | False | True |
2 | d17ca986-... | cf... | a69... | 1920 | 1080 | 140 | False | True | False |
where: - attachment_id - image file name without extension - user_id - unique anonymized user ID - data_hash - image hash by using Perceptual hashing - width - image width - height - image height - brightness - image brightness - train, test, valid are the binary columns for train / test / val subsets respectively
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Tina-target ng aming Eastern Asia Single-person Portrait Matting Dataset ang mga nuanced na kinakailangan ng sektor ng fashion, internet, at entertainment, na nagtatampok ng mga single-person na portrait mula sa Eastern Asia sa iba't ibang setting kabilang ang panloob, panlabas, kalye, at sport. Espesyal na na-curate ang dataset na ito para sa mga gawain sa fine segmentation sa antas ng pixel, na kumukuha ng magkakaibang postura at senaryo.
30,696 Pairs of Portrait Retouched Before and After Image Data. Data collection scenarios include indoor and outdoor scenes, the country distribution is Algeria, Egypt, Hungary, Poland, and Japan. Data types include portrait photos and wedding photos. In terms of data annotation, detailed retouching and annotationing are performed on the collected studio portrait data. The data can be used for tasks such as studio portrait retouching, PS segmentation, and portrait segmentation.
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Matting Dataset-ka-qofka-qofka ah waa agab muhiim u ah moodada, warbaahinta, iyo warshadaha warbaahinta bulshada, iyada oo bixisa sawiro sawir leh oo si fiican u calaamadsan kuwaas oo qabta qaab-dhismeedka iyo timo kala duwan oo kala duwan oo ka yimid wadamo kala duwan. Iyadoo diirada la saarayo sawirada qaraarka sare ee ka badan 1080 x 1080 pixels, xogtan waxa loo habeeyey codsiyada u baahan kala qaybsanaan tafatiran, oo ay ku jiraan timaha, dhegaha, faraha, iyo sifooyinka kale ee sawirka adag.
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Ny Dataset Portrait Matting ho an'ny olona tokana dia loharano lehibe ho an'ny indostrian'ny lamaody, ny haino aman-jery ary ny haino aman-jery sosialy, manome sary sariitatra misy marika tsara izay maka karazana fihetsika sy taovolo avy amin'ny firenena samihafa. Miaraka amin'ny fifantohana amin'ny sary avo lenta mihoatra ny 1080 x 1080 piksel, ity angon-drakitra ity dia namboarina ho an'ny fampiharana mitaky fizarana amin'ny antsipiriany, ao anatin'izany ny volo, sofina, rantsantanana, ary ireo endri-tsary saro-pady hafa.
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The self-portrait photo studio market is experiencing robust growth, projected to reach a market size of $6.45 billion in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 14.6% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the increasing popularity of social media platforms like Instagram and TikTok, where visually appealing self-portraits are crucial for personal branding and engagement, significantly drives demand. Secondly, technological advancements in photography equipment, including readily available high-quality cameras and user-friendly editing software, are making professional-quality self-portraits more accessible to a wider audience. Furthermore, the rise of experiential retail and the growing desire for personalized, memorable experiences are contributing to the market's growth. The diverse range of segments, encompassing half-length and full-length photo options across various locations like shopping malls and tourist attractions, caters to a broad consumer base. This versatility, coupled with the innovative business models adopted by companies like DON'T LXXK UP, Photoism Box, and Snapio, demonstrates the market's dynamic nature and its potential for further expansion. The market segmentation by photo type (half-length and full-length) and application (shopping malls, tourist attractions, and others) offers diverse revenue streams. The geographical distribution of the market, encompassing North America, Europe, Asia-Pacific, and other regions, reveals significant growth opportunities in emerging economies where disposable incomes are rising and the adoption of social media continues to accelerate. While challenges like competition from casual photography and fluctuating economic conditions could potentially constrain growth, the overall market outlook remains optimistic, driven by the enduring appeal of self-expression through photography and the ongoing evolution of technological advancements in this sector. The continued integration of innovative features, such as augmented reality filters and interactive elements, promises to further stimulate market growth in the coming years.
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Peb Ib Leeg Ib Tus Neeg Portrait Matting Dataset yog qhov tseem ceeb rau kev zam, xov xwm, thiab kev tshaj xov xwm kev lag luam, muab cov ntawv sau zoo nkauj zoo nkauj uas ntes tau ntau yam ntawm postures thiab hairstyles los ntawm ntau lub teb chaws. Nrog rau kev tsom mus rau cov duab daws teeb meem siab tshaj 1080 x 1080 pixels, cov ntaub ntawv no yog tsim los rau cov ntawv thov uas xav tau cov ncauj lus kom ntxaws segmentation, suav nrog plaub hau, pob ntseg, ntiv tes, thiab lwm yam sib txawv portrait nta.
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The family painting market, encompassing oil paintings, sketches, and other art forms, is a vibrant and growing sector. While precise market size data for 2025 is unavailable, considering the presence of numerous established companies like Drew Barrymore Flower Home, Marmont Hill, and Trademark Art, along with a diverse range of applications across living rooms, bedrooms, and kitchens, we can estimate the 2025 global market size to be approximately $500 million USD. This estimation considers the substantial presence of online retailers and physical art galleries catering to this segment, indicative of substantial demand. The Compound Annual Growth Rate (CAGR), though unspecified, is likely influenced by several factors. Increasing disposable incomes in developing economies, coupled with rising home décor spending and the growing popularity of personalized artwork, contribute positively to market expansion. However, potential restraints include fluctuations in raw material costs (e.g., canvas, paints) and the rising popularity of digital art, which could present a challenge to traditional formats. Segmentation reveals strong demand across various applications, with the living room likely leading as a primary area for family portrait displays and thematic artwork. The competitive landscape is marked by a mix of established brands and emerging artists, suggesting opportunities for both large-scale production and niche, bespoke art pieces. Regional variations in demand are expected, with North America and Europe likely holding larger market shares due to higher disposable incomes and established art markets. The forecast period (2025-2033) projects continued growth driven by the enduring appeal of family portraiture and the increasing preference for personalized wall art. The strategic focus for companies within this sector should be on offering diverse styles, sizes, and price points to cater to a broad customer base. Effective digital marketing and online retail presence will be crucial in reaching a wider audience, while maintaining a focus on quality and artistic expression. Expanding into emerging markets with rising affluence presents significant opportunities for growth. Further segmentation by artistic style (e.g., realism, impressionism) and subject matter can help tailor products to specific consumer preferences. Sustainable sourcing of materials and environmentally conscious production practices will resonate with increasingly eco-conscious consumers, offering a significant competitive advantage. Collaboration with interior designers and home décor influencers can further amplify brand reach and drive sales within the competitive market.
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The Portrait Photography Services market has seen significant growth and transformation over the years, adapting to the evolving demands of customers and advancements in technology. Portrait photography serves a vital role in capturing the essence of individuals, families, and professionals, offering a means to pres
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A large-scale video portrait dataset that contains 291 videos from 23 conference scenes with 14K frames. This dataset contains various teleconferencing scenes, various actions of the participants, interference of passers-by and illumination change.
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Ọwụwa Anyanwụ Eshia Single-Portrait Matting Dataset lekwasịrị anya n'ụzọ dị iche iche nke ejiji, ịntanetị, na mpaghara ntụrụndụ, na-egosipụta eserese otu onye sitere na Eastern Asia n'ọtụtụ ntọala gụnyere ime ụlọ, n'èzí, okporo ụzọ, na egwuregwu. A na-ahazi ihe ndekọ data a maka ọrụ nkewa dị mma nke ọkwa pikselụ, na-ewere ọnọdụ na ọnọdụ dị iche iche.
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Ny Dataset Portrait Matting an'ny olona tokana any Azia Atsinanana dia mikendry ireo fepetra takian'ny sehatry ny lamaody, aterineto ary fialamboly, ahitana sarin'olona tokana avy any Azia Atsinanana amin'ny sehatra isan-karazany ao anatin'izany ny anatiny, ivelany, an-dalambe ary ny fanatanjahantena. Ity angon-drakitra ity dia nokarakaraina manokana ho an'ny asa fizarazarana amin'ny ambaratonga piksel, misintona fihetsika sy toe-javatra samihafa.
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Isethi yethu yedatha yedatha yedatha ye-Portrait Matting yomuntu oyedwa yase-Eastern Asia iqondise izimfuneko eziguquguqukayo zemikhakha yemfashini, i-inthanethi, nezokungcebeleka, efaka izithombe zomuntu oyedwa ezivela e-Eastern Asia kuzilungiselelo ezihlukahlukene ezihlanganisa zasendlini, ngaphandle, emgwaqweni, nezemidlalo. Le dathasethi ikhethelwe ngokukhethekile imisebenzi yokuhlukanisa kahle yezinga le-pixel, ithwebula ukuma okuhlukahlukene nezimo.
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The Portrait Recognition Solar Simulator market is rapidly evolving as a crucial part of the solar energy industry, leveraging advanced portrait recognition technologies to optimize solar panel performance and installation processes. This innovative solution facilitates the identification of ideal solar panel placem
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Matting Dataset ɗinmu na Gabashin Asiya-Mutum ɗaya-mutumin yana yin niyya ga ƙayyadaddun bukatu na salon, intanit, da sassan nishaɗi, waɗanda ke nuna hotunan mutum ɗaya daga Gabashin Asiya a cikin saituna iri-iri ciki har da gida, waje, titi, da wasanni. Wannan saitin bayanan an keɓance shi musamman don kyawawan ayyuka na rarraba matakin-pixel, yana ɗaukar matsayi da yanayi iri-iri.
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The global stock photo market is a dynamic and rapidly expanding sector, projected to experience substantial growth over the next decade. While precise figures for market size and CAGR were not provided, leveraging industry reports and trends, a reasonable estimation can be made. Assuming a current market size (2025) of approximately $5 billion USD and a conservative Compound Annual Growth Rate (CAGR) of 8%, the market is poised for significant expansion. This growth is fueled by several key drivers: the increasing demand for high-quality visual content across various platforms (websites, social media, advertising, etc.), the rising adoption of digital marketing strategies, and the continuous improvement in image search and retrieval technologies. Furthermore, the ease of access to stock photography through subscription-based platforms and microstock agencies has democratized access to professional-grade imagery for both individuals and businesses. Several trends are shaping the market's future trajectory. The increasing popularity of mobile photography and user-generated content is creating a larger pool of available images. Simultaneously, the demand for more diverse and inclusive imagery is rising, pushing stock photo providers to broaden their offerings. However, challenges remain. Copyright issues, the proliferation of low-quality images, and competition among numerous providers are some of the restraining factors impacting market growth. Segmentation reveals that portrait, fashion, and editorial photography remain highly sought-after categories, while the application of stock photos in advertising and website building constitutes significant revenue streams. Key players like Getty Images, Shutterstock, and Adobe maintain dominant market positions, but emerging platforms and independent photographers are also contributing to the market's complexity and dynamic nature.
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I-Portrait Matting Dataset ibhekelela imikhakha yezingubo kanye nemidiya nezokuzijabulisa, ehlanganisa iqoqo elihlukahlukene lezithombe-skrini ezibukhoma ezinezinqumo ezisuka ku-138 × 189 kuye ku-6000 × 4000. Le dathasethi ibanzi, okuhlanganisa abantu abangabodwana, amaqembu, nezinsiza zabo, futhi inesichasiselo sesibonelo, ukuhlelwa nokuhlelwa.
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The global camera color effects filter market is experiencing robust growth, driven by the increasing popularity of photography and videography among both professionals and amateurs. The market, estimated at $500 million in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching approximately $900 million by 2033. This expansion is fueled by several key factors. The rise of social media platforms, where visually appealing content is paramount, has significantly boosted demand for filters that enhance image quality and create unique aesthetics. Furthermore, advancements in filter technology, including the development of more sophisticated color correction and creative effects, are driving market adoption. The prevalence of smartphones with high-quality cameras and readily available editing apps also contributes to this growth, making filter usage more accessible. While the online market segment currently holds the largest share, offline retail channels, particularly specialized camera stores, are expected to witness steady growth, reflecting the importance of hands-on experience in selecting filters for professional applications. The warm color filter segment dominates the market due to its wide applications in portrait and landscape photography, but the cool color filter segment is anticipated to see significant growth driven by increasing demand in specific genres like street photography and architectural shoots. Geographic segmentation reveals strong market presence in North America and Europe, driven by higher disposable income and technological advancement, while Asia Pacific is expected to witness accelerated growth in the coming years due to its rising middle class and expanding smartphone market. Challenges include intense competition from numerous filter manufacturers and the potential for market saturation in certain segments. The market segmentation shows a diverse landscape, with both online and offline channels contributing significantly to sales. The online segment's convenience and vast reach are attractive, while offline stores allow for physical product evaluation. In terms of filter types, warm color filters currently lead due to their versatility across photography styles, offering a classic and aesthetically pleasing effect. However, the cool color filter segment presents considerable future potential, given its artistic applications and increasing popularity among photographers seeking unique visual styles. Regional variations exist, with North America and Europe demonstrating strong established markets while Asia Pacific exhibits significant growth opportunities. The market's future hinges on continued technological innovation, catering to the evolving aesthetic preferences of photographers and videographers, and strategically addressing competitive pressures through product differentiation and targeted marketing campaigns. Maintaining sustainable growth will require a focus on quality, affordability, and the introduction of innovative filter designs that push creative boundaries.
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The pet photography market is experiencing robust growth, driven by increasing pet ownership, rising disposable incomes, and a growing desire among pet owners to commemorate their beloved companions. The market's emotional connection to pet owners fuels demand for high-quality, personalized pet photography services, extending beyond simple snapshots to encompass artistic, life-style, and professional shoots. While precise market size data is unavailable, considering the strong growth trends in related sectors like pet care and the increasing popularity of social media pet profiles, a reasonable estimate for the 2025 market size could be $500 million. Assuming a conservative Compound Annual Growth Rate (CAGR) of 10% (a figure that reflects moderate but steady expansion in line with overall consumer spending on pets), the market is projected to reach approximately $800 million by 2033. This growth is fueled by several key drivers, including the increasing humanization of pets, the rise of social media platforms like Instagram which showcase pet photography, the expansion of professional pet photography studios offering specialized services (like underwater or themed shoots), and growing consumer preference for unique and personalized products (custom calendars, pet portraits). Market segmentation reveals strong demand across both personal and commercial applications. Personal pet photography remains the largest segment, driven by individual pet owners' desire for lasting memories. However, the commercial segment, encompassing pet-related businesses utilizing professional photography for marketing and branding purposes, is also growing rapidly. Further segmentation by photography type (life photography, art photography, professional photography) reflects the market's diverse offering and caters to a broad spectrum of consumer preferences and budget levels. While challenges such as economic downturns and competition from amateur photographers exist, the overall market outlook remains positive, driven by the enduring bond between humans and their pets and the continued innovation within the pet photography industry. Geographic distribution shows robust growth across North America and Europe, with significant emerging markets in Asia-Pacific and other developing regions.
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Portrait Matting Dataset yana ba da kayan ado da kuma kafofin watsa labaru & sassan nishaɗi, yana nuna nau'i-nau'i daban-daban na raye-rayen hotuna masu rai tare da ƙuduri daban-daban daga 138 × 189 zuwa 6000 × 4000. Wannan bayanan yana da mahimmanci, ciki har da mutane guda ɗaya, ƙungiyoyi, da kayan haɗin su, kuma an ba da bayanin don contour, semantic task, da misali.
We introduce a large-scale image dataset EasyPortrait for portrait segmentation and face parsing. Proposed dataset can be used in several tasks, such as background removal in conference applications, teeth whitening, face skin enhancement, red eye removal or eye colorization, and so on.
EasyPortrait dataset size is about 26GB, and it contains 20 000 RGB images with high quality annotated masks. This dataset is divided into training set, validation set and test set by hashed subject user_id. The training set includes 14000 images, the validation set includes 2000 images, and the test set includes 4000 images.
Training images were received from 5,947 unique users, while validation was from 860 and testing was from 1,570. On average, each EasyPortrait image has 254 polygon points, from which it can be concluded that the annotation is of high quality. Segmentation masks were created from polygons for each annotation.
Annotations are presented as 2D-arrays, images in *.png format with several classes:
Index | Class |
---|---|
0 | BACKGROUND |
1 | PERSON |
2 | SKIN |
3 | LEFT BROW |
4 | RIGHT_BROW |
5 | LEFT_EYE |
6 | RIGHT_EYE |
7 | LIPS |
8 | TEETH |
Also, we provide some additional meta-information for dataset in annotations/meta.zip file:
attachment_id | user_id | data_hash | width | height | brightness | train | test | valid | |
---|---|---|---|---|---|---|---|---|---|
0 | de81cc1c-... | 1b... | e8f... | 1440 | 1920 | 136 | True | False | False |
1 | 3c0cec5a-... | 64... | df5... | 1440 | 1920 | 148 | False | False | True |
2 | d17ca986-... | cf... | a69... | 1920 | 1080 | 140 | False | True | False |
where: - attachment_id - image file name without extension - user_id - unique anonymized user ID - data_hash - image hash by using Perceptual hashing - width - image width - height - image height - brightness - image brightness - train, test, valid are the binary columns for train / test / val subsets respectively