LMM For Classification¶
Deprecated
This block is deprecated and may be removed in a future release.
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:
Email Notification,Contrast Equalization,Instance Segmentation Model,Google Vision OCR,Grid Visualization,S3 Sink,Stability AI Image Generation,Model Comparison Visualization,Absolute Static Crop,Keypoint Visualization,SIFT,Trace Visualization,Roboflow Dataset Upload,Twilio SMS/MMS Notification,QR Code Generator,Buffer,Model Monitoring Inference Aggregator,GLM-OCR,Reference Path Visualization,Halo Visualization,OCR Model,SIFT Comparison,VLM As Classifier,Image Preprocessing,Crop Visualization,OpenAI,OpenAI,Label Visualization,Classification Label Visualization,Pixelate Visualization,Local File Sink,Twilio SMS Notification,Email Notification,Qwen3.5-VL,Stitch OCR Detections,Corner Visualization,Stitch Images,Background Subtraction,Stitch OCR Detections,LMM For Classification,EasyOCR,Morphological Transformation,CSV Formatter,OpenAI,Clip Comparison,Image Threshold,Background Color Visualization,Anthropic Claude,Google Gemini,Camera Calibration,Halo Visualization,Stability AI Outpainting,Roboflow Custom Metadata,CogVLM,OpenAI,Single-Label Classification Model,Ellipse Visualization,Dynamic Zone,Heatmap Visualization,Image Convert Grayscale,Triangle Visualization,Image Blur,Depth Estimation,Size Measurement,Dimension Collapse,Color Visualization,Camera Focus,Text Display,Anthropic Claude,Dot Visualization,Image Slicer,Keypoint Detection Model,Polygon Visualization,Florence-2 Model,Motion Detection,Circle Visualization,Blur Visualization,Multi-Label Classification Model,Google Gemini,LMM,Slack Notification,Icon Visualization,Detections List Roll-Up,Camera Focus,Stability AI Inpainting,Polygon Visualization,Webhook Sink,Polygon Zone Visualization,Perspective Correction,Florence-2 Model,Anthropic Claude,Mask Visualization,Google Gemini,Image Contours,Dynamic Crop,Roboflow Dataset Upload,Llama 3.2 Vision,Clip Comparison,VLM As Detector,Object Detection Model,Image Slicer,Line Counter Visualization,Relative Static Crop,Bounding Box Visualization - outputs:
Detections Classes Replacement,Email Notification,Instance Segmentation Model,PTZ Tracking (ONVIF),Google Vision OCR,Contrast Equalization,S3 Sink,Stability AI Image Generation,Model Comparison Visualization,Keypoint Visualization,Trace Visualization,Roboflow Dataset Upload,Twilio SMS/MMS Notification,CLIP Embedding Model,QR Code Generator,SAM 3,GLM-OCR,Model Monitoring Inference Aggregator,Reference Path Visualization,Cache Set,Halo Visualization,SIFT Comparison,Time in Zone,Image Preprocessing,Perception Encoder Embedding Model,Crop Visualization,OpenAI,OpenAI,Label Visualization,Classification Label Visualization,Twilio SMS Notification,Local File Sink,Email Notification,Stitch OCR Detections,Corner Visualization,Time in Zone,Time in Zone,Stitch OCR Detections,LMM For Classification,Morphological Transformation,SAM 3,Path Deviation,Line Counter,OpenAI,Clip Comparison,Image Threshold,Background Color Visualization,Anthropic Claude,Google Gemini,Stability AI Outpainting,Halo Visualization,CogVLM,Roboflow Custom Metadata,OpenAI,Ellipse Visualization,Detections Stitch,Heatmap Visualization,Triangle Visualization,Cache Get,Size Measurement,Image Blur,Depth Estimation,Color Visualization,Text Display,Anthropic Claude,Dot Visualization,SAM 3,Polygon Visualization,Florence-2 Model,Circle Visualization,Google Gemini,LMM,Slack Notification,Icon Visualization,Stability AI Inpainting,Polygon Visualization,Webhook Sink,Polygon Zone Visualization,Florence-2 Model,Perspective Correction,Instance Segmentation Model,Anthropic Claude,Mask Visualization,Moondream2,Google Gemini,Roboflow Dataset Upload,Dynamic Crop,YOLO-World Model,Llama 3.2 Vision,Distance Measurement,Seg Preview,Pixel Color Count,Line Counter Visualization,Path Deviation,Line Counter,Bounding Box Visualization,Segment Anything 2 Model
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 whenlmm_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"
}