Clip Comparison

v2

Class: ClipComparisonBlockV2 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.foundation.clip_comparison.v2.ClipComparisonBlockV2

Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning

Use the OpenAI CLIP zero-shot classification model to classify images.

This block accepts an image and a list of text prompts. The block then returns the similarity of each text label to the provided image.

This block is useful for classifying images without having to train a fine-tuned classification model. For example, you could use CLIP to classify the type of vehicle in an image, or if an image contains NSFW material.

Type identifier

Use the following identifier in step "type" field: roboflow_core/clip_comparison@v2to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Unique name of step in workflows.	❌
classes	List[str]	List of classes to calculate similarity against each input image.	✅
version	str	Variant of CLIP model.	✅

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 Clip Comparison in version v2.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Clip Comparison in version v2 has.

Bindings

• input

  • images (image): The image to infer on..
  • classes (list_of_values): List of classes to calculate similarity against each input image.
  • version (string): Variant of CLIP model.

• output

  • similarities (list_of_values): List of values of any type.
  • max_similarity (float_zero_to_one): float value in range [0.0, 1.0].
  • most_similar_class (string): String value.
  • min_similarity (float_zero_to_one): float value in range [0.0, 1.0].
  • least_similar_class (string): String value.
  • classification_predictions (classification_prediction): Predictions from classifier.
  • parent_id (parent_id): Identifier of parent for step output.
  • root_parent_id (parent_id): Identifier of parent for step output.

Example JSON definition of step Clip Comparison in version v2

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/clip_comparison@v2",
    "images": "$inputs.image",
    "classes": [
        "a",
        "b",
        "c"
    ],
    "version": "ViT-B-16"
}

v1

Class: ClipComparisonBlockV1 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.foundation.clip_comparison.v1.ClipComparisonBlockV1

Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning

Use the OpenAI CLIP zero-shot classification model to classify images.

This block accepts an image and a list of text prompts. The block then returns the similarity of each text label to the provided image.

This block is useful for classifying images without having to train a fine-tuned classification model. For example, you could use CLIP to classify the type of vehicle in an image, or if an image contains NSFW material.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Unique name of step in workflows.	❌
texts	List[str]	List of texts to calculate similarity against each input image.	✅

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 Clip Comparison in version v1.

• inputs: OpenAI, Size Measurement, Buffer, Image Convert Grayscale, Florence-2 Model, Absolute Static Crop, Relative Static Crop, Label Visualization, Line Counter Visualization, Background Color Visualization, Stitch Images, Camera Focus, Image Contours, Image Preprocessing, Image Slicer, Reference Path Visualization, SIFT Comparison, Triangle Visualization, Grid Visualization, Polygon Zone Visualization, Keypoint Visualization, Depth Estimation, Llama 3.2 Vision, Dynamic Zone, Bounding Box Visualization, Image Blur, Perspective Correction, Halo Visualization, Clip Comparison, Ellipse Visualization, Color Visualization, Crop Visualization, Google Gemini, Dot Visualization, Pixelate Visualization, Model Comparison Visualization, Classification Label Visualization, Camera Calibration, Dimension Collapse, Stability AI Image Generation, Polygon Visualization, Trace Visualization, Corner Visualization, Image Threshold, Blur Visualization, Image Slicer, Clip Comparison, Stability AI Inpainting, Mask Visualization, SIFT, Anthropic Claude, Florence-2 Model, Circle Visualization, Dynamic Crop
• outputs: OpenAI, Size Measurement, Buffer, Path Deviation, Florence-2 Model, VLM as Detector, Label Visualization, Line Counter Visualization, Reference Path Visualization, Instance Segmentation Model, Keypoint Detection Model, Object Detection Model, Triangle Visualization, Path Deviation, Line Counter, Grid Visualization, Polygon Zone Visualization, Keypoint Visualization, LMM For Classification, Llama 3.2 Vision, Clip Comparison, Bounding Box Visualization, Perspective Correction, Halo Visualization, Google Gemini, Ellipse Visualization, Color Visualization, Crop Visualization, Object Detection Model, Webhook Sink, Dot Visualization, Email Notification, Instance Segmentation Model, Classification Label Visualization, YOLO-World Model, VLM as Detector, Cache Set, Polygon Visualization, Time in Zone, Time in Zone, Line Counter, Corner Visualization, Trace Visualization, VLM as Classifier, Clip Comparison, Keypoint Detection Model, Mask Visualization, Anthropic Claude, Florence-2 Model, VLM as Classifier, Circle Visualization, Detections Consensus

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Clip Comparison in version v1 has.

Bindings

• input

  • images (image): The image to infer on..
  • texts (list_of_values): List of texts to calculate similarity against each input image.

• output

  • similarity (list_of_values): List of values of any type.
  • parent_id (parent_id): Identifier of parent for step output.
  • root_parent_id (parent_id): Identifier of parent for step output.
  • prediction_type (prediction_type): String value with type of prediction.

Example JSON definition of step Clip Comparison in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/clip_comparison@v1",
    "images": "$inputs.image",
    "texts": [
        "a",
        "b",
        "c"
    ]
}