Egocentric Pet Grooming Salon Task Video Data

Egocentric pet grooming salon data is first-person video of grooming-salon work, recorded to a written skill spec so that a robot learning system can see how the work is done. In the task catalog the setting is called Pet Grooming Salon and sits in the Pet & Animal Care sector. Its example line reads "Pet grooming salon with washing tubs, grooming tables and drying stations". The same idea sits behind any pet grooming robot training data, grooming salon video dataset or egocentric pet grooming workflow data request, applied here as a custom grooming data collection scoped to your own steps.

On this site the data is human capture: a paid, consented contributor performs the task while the rig records it. It is not robot or teleoperation data. The catalog lists one capture mode for both grooming rows, a head-mounted phone or a multiview rig, and which of the two a program uses is agreed in the skill spec.

The catalog lists two rows for the Pet Grooming Salon environment. The first reads "Bathe, dry, trim, and brush pets’ coats and nails using pet shampoo, a grooming dryer, clippers, and brushes," with the description "Pet grooming salon with washing tubs, grooming tables, and drying stations." The second is named "Pet Grooming" and is described as "Washing, clipping, drying and grooming animals in a commercial grooming setting." Both are rated Medium.

Both rows are Active collection. The site defines that status as "Recording in this environment is running now, so a spec can join an existing capture stream." That is a statement about the catalog row, not a promise of a delivery date.

The first table lists both rows as the catalog states them. The second sorts the kinds of salon work a buyer might ask about. Washing, drying, trimming and brushing each appear in the stated row text. Grooming station setup, tool cleaning and reset, towel and linen handling, product restocking, tub or table wipe-down and kennel or crate reset have no row in this environment, so each is Not stated here. A kennel cleaning row exists in the veterinary clinic environment and is covered on its own page. If you need any of the unlisted steps, name them in the spec.

Each attempt at a task is delivered as one episode. The site’s episode schema lists action segments, contact events, 3D hand pose for both hands with a per-joint visibility flag, and instance masks, alongside int64 nanosecond timestamps per stream and camera intrinsics and extrinsics. Hand pose is stated as 21 joints per hand, in 3D, in metres in the head-camera frame.

The site’s general capture statement lists a head-mounted global-shutter 4K/60 camera with a 120° lens, two wrist-mounted 1080p/60 cameras, an active-stereo depth sensor at 848×480 and 30 fps, and 200 Hz 6-DoF IMUs, all hardware-triggered onto a single PTP clock domain. It describes ten synchronized streams aligned under 2 ms. Which of those streams a grooming program carries is Not stated for this environment, because the grooming rows list a head-mounted phone or multiview rig, and it is decided in the skill spec.

Action segments divide an episode into start- and end-timestamped spans, each carrying start_ns, end_ns, verb and noun, aligned to every other stream. The site states the verb and noun taxonomy as 97 verbs and 512 nouns, human-reviewed. For grooming, a segment might be one wash, one dry pass, one trim or one brush pass, as the skill spec defines it. A spec that says "groom the pet" gives you one long segment, while a spec that names the steps gives you a sequence you can slice. Contact events mark when a hand meets an item; the site does not describe them as force or pressure.

Validation runs against accept criteria written into the spec before capture. A reject log ships with each batch, and only footage that clears the criteria counts as a validated hour. The site states these reject thresholds: a cross-stream sync error above a 2.0 ms ceiling, the manipulated object out of frame for more than 15 percent of the episode, and more than 35 percent invalid depth pixels in the manipulation region. On custom collection engagements, rejected items are recaptured at the provider’s cost, and delivery is billed per validated hour, not per raw hour recorded. These are reject thresholds, not a stated pass rate or yield; no pass rate is stated.

Delivery is in the format your stack already reads: RLDS, LeRobot, WebDataset, HDF5, zarr or Rerun .rrd, with converters shipped as readable source so you can retarget the schema to your own loader. The official RLDS repository describes datasets as episodes made of steps. The official LeRobot repository describes its dataset format as synchronized MP4 videos or images plus Parquet files for state and action data. Whether a grooming delivery carries robot action data is Not stated; the site describes human-side capture only.

The license is perpetual, irrevocable and buyer-owned, and non-exclusive by default, with exclusivity available as a separate term. The executed agreement controls.

Grooming changes the tool in the hand at almost every step. The catalog row names a shampoo, a dryer, clippers and brushes, so the order of the steps and which hand holds what carry much of the value. First-person capture keeps the hands in frame from the operating viewpoint, and 3D hand pose carries a per-joint visibility flag, so a finger hidden behind a coat or a tool is flagged rather than guessed.

The work is also done around a living subject in the catalog’s own words: "pets’ coats and nails" and "animals". The site states nothing about how a coat, water or a moving animal affects any stream, and no accuracy figure. The table below maps each difficulty to what the site states.

The site also states no success or quality label for a groom. A buyer who needs one has to write it into the skill spec as an accept criterion. Firsthand captures humans, not robots, so using the episodes for a specific robot means your own retargeting step.

The catalog describes the setting as a salon "with washing tubs, grooming tables and drying stations" and the second row as a "commercial grooming setting." It does not say whether the salon is a working business or a staged set, and it does not say whether the animals in these rows are live animals, animal models or props. This page claims none of those, and the spec states which applies. The site also states that capture happens in Firsthand’s contributor settings, not at a customer’s own facility. Which venue or region a program uses is Not stated and is agreed in the skill spec.

Every contributor signs a written release granting commercial training rights before capture begins, and is paid a published hourly rate rather than a per-task bounty. Consent is tracked through a signed consent chain, and each delivered episode links to it. Faces and screens are detected and blurred irreversibly, a human reviewer confirms that no un-consented person is identifiable, and footage with bystanders who cannot be de-identified is discarded rather than shipped. The anonymization record ships with the data.

The site does not state how animal owners, clients or other staff in a salon are handled beyond that general bystander rule. It makes no animal-welfare, animal-handling, health, safety-compliance or certification claim. Settle all of these in the spec before capture. This is not legal advice, and the executed agreement controls.

From signed spec to first validated batch, the published timeline is a median of 48 hours in environments where coverage is already deep, and three to four weeks where coverage is thin and contributors need to be vetted and recruited first. Both grooming rows are listed as Active collection, which the site defines as recording that is running now, so a spec can join an existing capture stream. The site does not say whether that makes the salon a deep-coverage environment, so which range applies is confirmed when your spec is quoted rather than assumed.

Describe the grooming steps and their order, how each step starts and ends, what counts as a finished step, the privacy rule for the space and the variation cases your pipeline is missing. That becomes a written skill spec, quoted for reach, timeline and price before any capture begins. Our skill spec guide walks through how to write one.

Most programs begin with a Spec Pilot, a small, fast first batch that proves the spec and the accept criteria on real footage before volume scales. Collections are billed per validated hour. Then request a custom dataset.