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.

Our Single-person Portrait Matting Dataset is a pivotal resource for the fashion, media, and social media industries, providing finely labeled portrait images that capture a wide range of postures and hairstyles from various countries. With a focus on high-resolution images exceeding 1080 x 1080 pixels, this dataset is tailored for applications requiring detailed segmentation, including hair, ears, fingers, and other intricate portrait features.

Dataset Card for AISegment.cn - Matting Human datasets

  Dataset Description

Quoting the dataset's github (translated by Apple Translator):

This dataset is currently the largest portrait matting dataset, containing 34,427 images and corresponding matting results. The data set was marked by the high quality of Beijing Play Star Convergence Technology Co. Ltd., and the portrait soft segmentation model trained using this data set has been commercialized.

The original images… See the full description on the dataset page: https://huggingface.co/datasets/fredguth/aisegmentcn-matting-human.

The school photography services market, currently valued at $24.8 billion in 2025, is projected to experience robust growth, exhibiting a compound annual growth rate (CAGR) of 5.4% from 2025 to 2033. This expansion is driven by several key factors. Increasing parental demand for high-quality professional photographs to document their children's academic milestones fuels market growth. The rise of digital platforms and social media further encourages the purchase of these services, as parents readily share these cherished memories online. Furthermore, schools themselves increasingly recognize the value of professional photography in enhancing their marketing materials and creating lasting memories for students and families. The market segmentation, encompassing various application levels (kindergarten through senior high school) and photography types (group and individual portraits), presents opportunities for specialized service providers to cater to niche demands. Competitive dynamics are shaped by established players like Lifetouch and Jostens alongside smaller, regional studios, creating a diverse and dynamic market landscape. Challenges include managing fluctuating student populations and adapting to evolving technological advancements in photography equipment and digital delivery methods. The geographical distribution of the market demonstrates significant regional variations. North America, with its established education system and higher disposable incomes, likely commands a substantial market share. However, rapidly developing economies in Asia-Pacific, particularly China and India, are poised for significant growth due to rising middle-class incomes and increasing awareness of professional photography services. Europe maintains a steady market presence, while the Middle East & Africa and South America show promising, albeit slower, growth trajectories. Future growth will depend on factors such as the continued penetration of digital technologies in educational institutions, innovations in photography services, and effective marketing strategies targeting parents and schools. The overall outlook for the school photography services market remains positive, indicating a promising investment opportunity for businesses willing to adapt to evolving consumer preferences and technological advancements.

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.

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.

The Rotatable Portrait Display market has emerged as a vital component in various industries, providing unique solutions for dynamic content presentation. These displays, designed for the ability to switch between landscape and portrait orientations, cater to diverse applications ranging from retail advertising to d

The Portrait Photography Service market has evolved into a dynamic and essential sector within the broader photography industry, catering to a diverse clientele that includes families, individuals, professionals, and businesses seeking to create lasting visual memories. This market encompasses a range of services, f

The photographic services market, valued at $46.71 billion in 2025, is projected to experience steady growth, with a compound annual growth rate (CAGR) of 2.6% from 2025 to 2033. This growth is fueled by several key factors. The increasing popularity of social media platforms like Instagram and Facebook, coupled with a rising demand for high-quality professional photographs for personal and commercial use, are significant drivers. Furthermore, advancements in digital photography technology, including improved camera sensors and readily available editing software, have lowered the barrier to entry for both consumers and businesses, contributing to market expansion. The market is witnessing a shift towards specialized services, including drone photography, 360° virtual tours, and photo restoration, catering to the evolving needs of various client segments. Competition is relatively high, with established players like Lifetouch, Getty Images, and others vying for market share. Pricing strategies and the ability to offer innovative and personalized services are crucial for success within this competitive landscape. The market segmentation is likely diverse, encompassing areas such as event photography (weddings, corporate events), portrait photography (family, individual), commercial photography (product shots, advertising), and specialized niche services as mentioned above. Regional variations in market growth will likely exist, influenced by factors such as disposable income, technological adoption rates, and cultural preferences. Geographic regions with strong economies and high digital literacy are expected to show faster growth compared to others. While the increasing accessibility of digital photography tools presents a potential restraint, the continued demand for professional expertise and high-quality results ensures the ongoing relevance and growth potential of the photographic services market. The forecast period reveals a promising outlook for businesses capable of adapting to evolving technological advancements and consumer preferences.

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.

Synthetic Faces High Quality (SFHQ) part 4

This dataset consists of 125,754 high quality 1024x1024 curated face images, and was created by first creating large amount of "text to image" generations (most from stable diffusion v2.1, some from stable diffusion v1.4) model and then creating several photo-realistic candidate images using a process similar to what is described in this short twitter thread which involve encoding the images into StyleGAN2 latent space and performing a small manipulation that turns each image into a high quality photo-realistic image candidate. Finally, we then sift through the resulting candidate images and keep only the good ones for the dataset.

The dataset also contains facial landmarks (extended set) and face parsing semantic segmentation maps. An example script is provided and demonstrates how to access landmarks, segmentation maps, and textually search withing the dataset (with CLIP image/text feature vectors), and also performs some exploratory analysis of the dataset. link to github repo of the dataset.

The process that corrects images generated by stable-diffusion and creates several candidate photo-realistic images is illustrated below: https://raw.githubusercontent.com/SelfishGene/SFHQ-dataset/main/images/bring_to_life_process_stable_diffusion.jpg" alt="">

More Details

1. The original inspiration images are generated images using stable diffusion v2.1 model (mostly) and using various face portrait prompts that span a wide range of ethnicities, ages, expressions, hairstyles, etc. Note that stable diffusion faces often contain errors in the generation so cannot be used to create a photo-reallistic dataset without a correcting model or an extremely lengthy manual curation process. we do both here.
2. Each inspiration image was encoded by encoder4editing (e4e) into StyleGAN2 latent space (StyleGAN2 is a generative face model tained on FFHQ dataset) and multiple candidate images were generated from each inspiration image
3. These candidate images were then further curated and verified as being photo-realistic and high quality by a single human (me) and a machine learning assistant model that was trained to approximate my own human judgments and helped me scale myself to asses the quality of all images in the dataset
4. Near duplicates and images that were too similar were removed using CLIP features (no two images in the dataset have CLIP similarity score of greater than ~0.9)
5. From each image various pre-trained features were extracted and provided here for convenience, in particular CLIP features for fast textual query of the dataset
6. From each image, semantic segmentation maps were extracted using Face Parsing BiSeNet and are provided in the dataset under "segmentations"
7. From each image, an extended landmark set was extracted that also contain inner and outer hairlines (these are unique landmarks that are usually not extracted by other algorithms). These landmarks were extracted using Dlib, Face Alignment and some post processing of Face Parsing BiSeNet and are provided in the dataset under "landmarks"
8. NOTE: semantic segmentation and landmarks were first calculated on scaled down version of 384x384 images, and then upscaled to 1024x1024

Parts 1,2,3,4

• Part 1 of the dataset consists of 89,785 HQ 1024x1024 curated face images. It uses "inspiration" images from Artstation-Artistic-face-HQ dataset (AAHQ), Close-Up Humans dataset and UIBVFED dataset.
• Part 2 of the dataset consists of 91,361 HQ 1024x1024 curated face images. It uses "inspiration" images from Face Synthetics dataset and by sampling from the Stable Diffusion v1.4 text to image generator using varied face portrait prompts.
• Part 3 of the dataset consists of 118,358 HQ 1024x1024 curated face images. It uses "inspiration" images by sampling from [StyleGAN2](https://git...

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

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

The Portrait Retouching Software market has experienced significant growth in recent years, driven by the increasing demand for high-quality photographic content across various industries, including fashion, beauty, e-commerce, and social media. This software allows photographers, graphic designers, and content crea

About

The dataset contains synthetically generated images of people wearing glasses (regular eyeglasses + sunglasses) and glasses masks (full + frames + shadows). It can primarily be used for eyeglasses/sunglasses classification and segmentation.

This dataset is an augmented version of the synthetic dataset introduced in Portrait Eyeglasses and Shadow Removal by Leveraging 3D Synthetic Data and can be accessed here. The augmentation adds overlays on top of eyeglass frames to create images of people wearing sunglasses and corresponding masks.

Structure

There are 73 people identities in total, each with 400 different expressions or lightning effects, thus making a total of 29,000 samples. Each sample is a group of 8 images of the form sample-name-[suffix].png where [suffix] can be one of the following: * all - regular eyeglasses (i.e., frames) and their shadows * sunglasses - occluded glasses (i.e., sunglasses) and their frame shadows * glass - regular eyeglasses but no shadows * shadows - frame shadows but no eyeglasses * face - plain face: no glasses and no shadows * seg - mask for regular eyeglasses * sgseg - mask for sunglasses * shaseg - mask for frame shadows

10 identities were used for test data and 10 identities for validation, which corresponds to roughly 14% each, leaving around 72% of the data for training (which is 21,200 samples).

Collection

The data was generated in the following process: 1. The original dataset was downloaded from the link in the official Github repository 2. Glasses Detector was used to create full glasses segmentation masks which were used to generate various color and transparency (mainly dark) glasses 3. The generated glasses were overlaid on top of the original images with frames to create new images with sunglasses and corresponding masks 4. The 73 identities were shuffled and split into 3 parts (train, val, test) which were used to group all the 400 variations of each identity.

You can see the full process of glass overlay generation and data splitting in this gist.

Note: a type of noise (e.g., random, single spot) was added to roughly 15% of the images with sunglasses. Also, some of the generated glasses do not fill the entire frame, however, masks capture that.

Licence

This dataset is marked under CC BY-NC 4.0, meaning you can share and modify the data for non-commercial reuse as long as you provide a copyright notice.

Citation

Please use the original authors, i.e., the following citation:

@misc{glasses-segmentation-synthetic,
  author = {Junfeng Lyu, Zhibo Wang, Feng Xu},
  title = {Glasses Segmentation Synthetic Dataset},
  year = {2023},
  publisher = {Kaggle},
  journal = {Kaggle datasets},
  howpublished = {\url{https://www.kaggle.com/datasets/mantasu/glasses-segmentation-synthetic-dataset}}
}

The AI Portrait Generator market is rapidly evolving, driven by advancements in artificial intelligence and machine learning technologies. This innovative segment leverages deep learning algorithms to create stunning, lifelike portraits from simple inputs, opening new avenues for artists, businesses, and individuals

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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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