LMM For Classification

Class: LMMForClassificationBlockV1

Source: inference.core.workflows.core_steps.models.foundation.lmm_classifier.v1.LMMForClassificationBlockV1

Classify an image into one or more categories using a Large Multimodal Model (LMM).

You can specify arbitrary classes to an LMMBlock.

The LLMBlock supports two LMMs:

• OpenAI's GPT-4 with Vision.

You need to provide your OpenAI API key to use the GPT-4 with Vision model.

Type identifier

Use the following identifier in step "type" field: roboflow_core/lmm_for_classification@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
lmm_type	str	Type of LMM to be used.	✅
classes	List[str]	List of classes that LMM shall classify against.	✅
lmm_config	LMMConfig	Configuration of LMM.	❌
remote_api_key	str	Holds API key required to call LMM model - in current state of development, we require OpenAI key when lmm_type=gpt_4v..	✅

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Compatible Blocks

Check what blocks you can connect to LMM For Classification in version v1.

• inputs: Grid Visualization, Image Blur, Image Preprocessing, Image Slicer, OpenAI, Dynamic Crop, Absolute Static Crop, Roboflow Dataset Upload, Color Visualization, LMM, Corner Visualization, Google Gemini, Depth Estimation, Stability AI Outpainting, Keypoint Visualization, Trace Visualization, Clip Comparison, Google Vision OCR, Keypoint Detection Model, Single-Label Classification Model, Email Notification, Model Comparison Visualization, Dimension Collapse, Mask Visualization, Image Slicer, Model Monitoring Inference Aggregator, Clip Comparison, Size Measurement, Multi-Label Classification Model, Buffer, Image Threshold, Contrast Equalization, OpenAI, Morphological Transformation, Classification Label Visualization, Relative Static Crop, Camera Calibration, Dynamic Zone, Florence-2 Model, Blur Visualization, Stitch Images, Roboflow Dataset Upload, Triangle Visualization, Perspective Correction, SIFT, Icon Visualization, Label Visualization, Stability AI Image Generation, Stitch OCR Detections, CogVLM, Ellipse Visualization, Llama 3.2 Vision, VLM as Detector, Line Counter Visualization, Florence-2 Model, SIFT Comparison, Local File Sink, Slack Notification, Image Convert Grayscale, Roboflow Custom Metadata, Twilio SMS Notification, Background Color Visualization, VLM as Classifier, QR Code Generator, Polygon Zone Visualization, Anthropic Claude, Polygon Visualization, Camera Focus, Dot Visualization, LMM For Classification, Instance Segmentation Model, Circle Visualization, Bounding Box Visualization, Image Contours, OpenAI, Object Detection Model, OCR Model, Halo Visualization, Reference Path Visualization, CSV Formatter, Pixelate Visualization, Webhook Sink, EasyOCR, Stability AI Inpainting, Crop Visualization
• outputs: Image Blur, OpenAI, Image Preprocessing, Instance Segmentation Model, Dynamic Crop, Time in Zone, Roboflow Dataset Upload, LMM, Moondream2, Color Visualization, Corner Visualization, Google Gemini, Stability AI Outpainting, Keypoint Visualization, PTZ Tracking (ONVIF).md), Trace Visualization, Clip Comparison, Google Vision OCR, Email Notification, YOLO-World Model, Time in Zone, Model Comparison Visualization, Mask Visualization, Model Monitoring Inference Aggregator, Size Measurement, Image Threshold, Contrast Equalization, Line Counter, OpenAI, Path Deviation, Morphological Transformation, Classification Label Visualization, Time in Zone, Path Deviation, Florence-2 Model, Cache Set, Roboflow Dataset Upload, Triangle Visualization, Perspective Correction, Icon Visualization, Label Visualization, Pixel Color Count, Stability AI Image Generation, Stitch OCR Detections, Llama 3.2 Vision, Ellipse Visualization, CogVLM, Line Counter Visualization, Florence-2 Model, Line Counter, Local File Sink, Distance Measurement, Slack Notification, SIFT Comparison, Roboflow Custom Metadata, Perception Encoder Embedding Model, Twilio SMS Notification, Background Color Visualization, QR Code Generator, Segment Anything 2 Model, Cache Get, Polygon Zone Visualization, Anthropic Claude, Detections Stitch, Polygon Visualization, Dot Visualization, LMM For Classification, CLIP Embedding Model, Detections Classes Replacement, Instance Segmentation Model, Circle Visualization, Bounding Box Visualization, OpenAI, Halo Visualization, Reference Path Visualization, Webhook Sink, Stability AI Inpainting, Crop Visualization

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds LMM For Classification in version v1 has.

Bindings

• input

  • images (image): The image to infer on..
  • lmm_type (string): Type of LMM to be used.
  • classes (list_of_values): List of classes that LMM shall classify against.
  • remote_api_key (Union[secret, string]): Holds API key required to call LMM model - in current state of development, we require OpenAI key when lmm_type=gpt_4v..

• output

  • raw_output (string): String value.
  • top (top_class): String value representing top class predicted by classification model.
  • parent_id (parent_id): Identifier of parent for step output.
  • root_parent_id (parent_id): Identifier of parent for step output.
  • image (image_metadata): Dictionary with image metadata required by supervision.
  • prediction_type (prediction_type): String value with type of prediction.

Example JSON definition of step LMM For Classification in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/lmm_for_classification@v1",
    "images": "$inputs.image",
    "lmm_type": "gpt_4v",
    "classes": [
        "a",
        "b"
    ],
    "lmm_config": {
        "gpt_image_detail": "low",
        "gpt_model_version": "gpt-4o",
        "max_tokens": 200
    },
    "remote_api_key": "xxx-xxx"
}