# Pretrained Models & Abilities This guide helps you build and run *Composable Pops*. They are configurable chains of AI tasks like object detection, OCR, pose estimation, and tracking all using the EyePop SDK. ### What Are Composable Pops? Composable Pops are dynamic pipelines that link multiple AI components together. Each component can perform inference, forward cropped regions to other models, or trace objects over time. With this system, you can chain object detection → cropping → pose estimation → tracking… and more. *** ### Anatomy of a Pop A Pop is defined with a list of components, each specifying: • **type**: the kind of processing (INFERENCE, TRACING, CONTOUR\_FINDER) • **inferenceTypes**: what to infer (e.g. OBJECT\_DETECTION, OCR) • **modelUuid / ability**: this specificies the model or ability to use • **forward**: what to do with the output (e.g. crop, trace, or chain more components) ### Available Models & Abilities All EyePop models are available as abilities by appending `:latest` to the model name. Use these in your Pop components with the `ability` parameter: ```json { type: PopComponentType.INFERENCE, ability: "eyepop.person:latest" } ``` #### Abilities Hub * Search a full list of all abilities here: * Create your own Abilities with a prompt on your [EyePop.ai Dashboard](https://dashboard.eyepop.ai/dashboard) #### Object Detection & Classification * `eyepop.common-objects:latest` - Detect common everyday objects\ Labels: `eyepop logo, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, fire hydrant, stop sign, parking meter, cat, dog, horse, umbrella, handbag, suitcase, sports ball, baseball bat, baseball glove, skateboard, surfboard, tennis racket, bottle, wine glass, cup, bowl, hot dog, chair, couch, potted plant, bed, dining table, toilet, tv, microwave, sink, refrigerator, book, laptop, mouse, remote, keyboard, cell phone, clock, scissors, hair drier, toothbrush` * `eyepop.animal:latest` - Animal detection and classification\ Labels: `bird, cat, dog, horse, sheep, cow, elephant, bear, zebra, giraffe` * `eyepop.vehicle:latest` - Vehicle detection\ Labels: `bicycle, car, motorcycle, bus, train, truck` * `eyepop.vehicle.license-plate:latest` - License Plate Detection\ Labels: `license-plate` * `eyepop.device:latest` - Electronic device detection\ Labels: `clock, laptop, mouse, remote, keyboard, cell phone` * `eyepop.sports:latest` - Sports equipment and activity detection\ Labels: `frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, surfboard, tennis racket` * `eyepop.localize-objects:latest` - Find objects with just a prompt. #### Person Analysis * `eyepop.person:latest` - Person detection\ Label: `person` * `eyepop.expression:latest` - Facial expression analysis\ Labels: `Happy, Neutral, Sad, Surprise, Angry, Fear, Disgust` * `eyepop.person.pose:latest` - Human pose estimation * `eyepop.person.2d-body-points:latest` - 2D body keypoint detection\ Labels: `left eye, left ear, left shoulder, left hip, left elbow, left wrist, left knee, left ankle, right eye, right ear, right shoulder, right hip, right elbow, right wrist, right knee, right ankle, nose, midpoint_lowest, midpoint_highest` * `eyepop.person.3d-body-points.full:latest` - Full 3D body pose * `eyepop.person.3d-body-points.heavy:latest` - Heavy 3D body pose model * `eyepop.person.3d-body-points.lite:latest` - Lightweight 3D body pose * `eyepop.person.3d-hand-points:latest` - 3D hand keypoint detection\ Labels: `mouth (right), mouth (left), right ear, right eye (outer), right eye, right eye (inner), nose, left eye (inner), left eye, left eye (outer), left ear, right shoulder, left shoulder, left hip, right hip, right elbow, right wrist, right thumb, right pinky, right index, left elbow, left wrist, left thumb, left pinky, left index, right knee, right ankle, right foot index, right heel, left knee, left ankle, left foot index, left heel` * `eyepop.person.face-mesh:latest` - Detailed facial mesh * `eyepop.person.face.long-range:latest` - Face detection for distant subjects * `eyepop.person.face.short-range:latest` - Face detection for close subjects * `eyepop.person.palm:latest` - Palm detection * `eyepop.person.reid:latest` - Person re-identification * `eyepop.person.segment:latest` - Person segmentation #### Text Recognition * `eyepop.text:latest` - Text detection * `eyepop.text.recognize.landscape:latest` - OCR for landscape text * `eyepop.text.recognize.landscape-tiny:latest` - Lightweight landscape OCR * `eyepop.text.recognize.square:latest` - OCR for square/document text * See the [Abilities Hub](https://www.eyepop.ai/abilities) for more structured OCR abilities. #### Quick Reference ```javascript // Common usage patterns // Detect people { type: PopComponentType.INFERENCE, ability: "eyepop.person:latest", confidenceThreshold: 0.8 } // Visual intelligence { type: PopComponentType.INFERENCE, ability: "eyepop.image-contents:latest", params: { prompts: [{ prompt: "What is this person wearing?" }] } } // Custom object labels { type: PopComponentType.INFERENCE, ability: "eyepop.localize-objects:latest", params: { prompts: [ {prompt: 'dog', label: 'Best Friend'} ] } } ``` *** #### Example Pops 1\. Text on Detected Objects ```javascript { components: [{ type: PopComponentType.INFERENCE, inferenceTypes: [InferenceType.OBJECT_DETECTION], ability: 'eyepop.common-objects:latest', forward: { operator: { type: ForwardOperatorType.CROP }, targets: [{ type: PopComponentType.INFERENCE, inferenceTypes: [InferenceType.OBJECT_DETECTION], ability: 'eyepop.text:latest', forward: { operator: { type: ForwardOperatorType.CROP }, targets: [{ type: PopComponentType.INFERENCE, inferenceTypes: [InferenceType.OCR], ability: 'PARSeq:latest' }] } }] } }] } ``` Use case: Extract text *within* labeled objects. *** 2\. Object Tracking ```javascript { components: [{ type: PopComponentType.INFERENCE, inferenceTypes: [InferenceType.OBJECT_DETECTION], ability: 'eyepop.common-objects:latest', forward: { operator: { type: ForwardOperatorType.CROP }, targets: [{ type: PopComponentType.TRACING }] } }] } ``` Use case: Detect and track object movements across frames. *** 3\. Detect Objects and Pose on People ```javascript { components: [ { type: PopComponentType.INFERENCE, inferenceTypes: [InferenceType.OBJECT_DETECTION], ability: 'eyepop.common-objects:latest', }, { type: PopComponentType.INFERENCE, inferenceTypes: [InferenceType.OBJECT_DETECTION], ability: "eyepop.person:latest", categoryName: 'person', confidenceThreshold: 0.8, forward: { operator: { type: ForwardOperatorType.CROP }, targets: [{ type: PopComponentType.INFERENCE, inferenceTypes: [InferenceType.KEY_POINTS], categoryName: '2d-body-points', ability: 'eyepop.person.2d-body-points:latest' }] } } ] } ``` Use case: Detect all objects and analyze human posture when a person is found. *** 4\. Segmentation and Contour Extraction ```javascript const OBJECT_SEGMENTATION = { components: [{ type: PopComponentType.INFERENCE, inferenceTypes: [InferenceType.OBJECT_DETECTION], ability: 'eyepop.common-objects:latest', forward: { operator: { type: ForwardOperatorType.CROP, crop: { boxPadding: 0.25 } }, targets: [{ type: PopComponentType.INFERENCE, inferenceTypes: [InferenceType.SEMANTIC_SEGMENTATION], modelUuid: 'EfficientSAM:latest', forward: { operator: { type: ForwardOperatorType.FULL }, targets: [{ type: PopComponentType.CONTOUR_FINDER, contourType: ContourType.POLYGON }] } }] } }] } ``` Use case: Get polygon contours of detected objects for precise shape/area analysis. *** Running the Pop ```javascript const endpoint = await EyePop.workerEndpoint(auth: { API_KEY }).connect() await endpoint.changePop(<'YOUR POP DEFINITION'>) const results = await endpoint.process({ path: 'image.jpg' }) for await (const result of results) { Render2d.renderer(ctx, [Render2d.renderPose(), Render2d.renderText(), Render2d.renderContour()]) .draw(result) } ``` #### Tips for Building Your Own Pops • Chain components by specifying forward.targets • Use ForwardOperatorType.CROP to pass cropped regions • Use categoryName and confidenceThreshold to filter by label • Use TRACING or CONTOUR\_FINDER for post-processing Contact us at or on our discord for any help creating a composable pop! --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.eyepop.ai/developer-documentation/sdks/pretrained-models-and-abilities.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.