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:
Image Slicer,Stability AI Inpainting,Clip Comparison,Perspective Correction,Object Detection Model,Roboflow Custom Metadata,SIFT Comparison,Grid Visualization,Ellipse Visualization,SIFT,CogVLM,VLM as Detector,Image Contours,OpenAI,Absolute Static Crop,Camera Focus,Polygon Visualization,Trace Visualization,Multi-Label Classification Model,Dot Visualization,Clip Comparison,Google Vision OCR,Polygon Zone Visualization,Roboflow Dataset Upload,Classification Label Visualization,Corner Visualization,Llama 3.2 Vision,Dynamic Crop,Reference Path Visualization,Label Visualization,Mask Visualization,Triangle Visualization,Line Counter Visualization,Dynamic Zone,Model Monitoring Inference Aggregator,Blur Visualization,Anthropic Claude,Webhook Sink,Instance Segmentation Model,Slack Notification,Stitch OCR Detections,Pixelate Visualization,Relative Static Crop,Twilio SMS Notification,Dimension Collapse,VLM as Classifier,Roboflow Dataset Upload,Google Gemini,Model Comparison Visualization,Halo Visualization,Crop Visualization,Image Blur,Circle Visualization,Buffer,Keypoint Detection Model,Image Preprocessing,Background Color Visualization,Size Measurement,Florence-2 Model,Bounding Box Visualization,Florence-2 Model,Local File Sink,Image Slicer,LMM For Classification,Stitch Images,Stability AI Image Generation,Image Threshold,OCR Model,LMM,Keypoint Visualization,Email Notification,Color Visualization,Single-Label Classification Model,CSV Formatter,Image Convert Grayscale,OpenAI - outputs:
Cache Set,Object Detection Model,Object Detection Model,Grid Visualization,Ellipse Visualization,CogVLM,CLIP Embedding Model,Dot Visualization,Clip Comparison,Google Vision OCR,Identify Changes,Polygon Zone Visualization,Classification Label Visualization,Corner Visualization,Dynamic Crop,Label Visualization,Detections Stabilizer,Triangle Visualization,Time in Zone,Line Counter,Webhook Sink,Instance Segmentation Model,Path Deviation,Relative Static Crop,Detections Consensus,Twilio SMS Notification,Crop Visualization,Distance Measurement,Circle Visualization,Keypoint Detection Model,Size Measurement,Single-Label Classification Model,Bounding Box Visualization,LMM For Classification,Image Threshold,Detections Stitch,Keypoint Visualization,Single-Label Classification Model,Detections Classes Replacement,Polygon Visualization,Segment Anything 2 Model,Image Slicer,Cache Get,Stability AI Inpainting,Clip Comparison,Perspective Correction,Roboflow Custom Metadata,SIFT Comparison,VLM as Detector,Multi-Label Classification Model,OpenAI,Trace Visualization,Multi-Label Classification Model,VLM as Detector,Identify Outliers,Roboflow Dataset Upload,VLM as Classifier,Llama 3.2 Vision,Byte Tracker,Line Counter,Reference Path Visualization,Mask Visualization,Line Counter Visualization,Template Matching,Model Monitoring Inference Aggregator,Anthropic Claude,Time in Zone,Instance Segmentation Model,Slack Notification,VLM as Classifier,Keypoint Detection Model,Roboflow Dataset Upload,Google Gemini,Model Comparison Visualization,Halo Visualization,Byte Tracker,Image Blur,Buffer,Image Preprocessing,Background Color Visualization,Pixel Color Count,Florence-2 Model,Florence-2 Model,Byte Tracker,Image Slicer,Local File Sink,Stitch Images,Stability AI Image Generation,LMM,Email Notification,Color Visualization,Path Deviation,YOLO-World Model,OpenAI
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):floatvalue in range[0.0, 1.0].most_similar_class(string): String value.min_similarity(float_zero_to_one):floatvalue 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:
Image Slicer,Stability AI Inpainting,Pixelate Visualization,Perspective Correction,Clip Comparison,OpenAI,Relative Static Crop,Dimension Collapse,SIFT Comparison,Google Gemini,Grid Visualization,Ellipse Visualization,SIFT,Model Comparison Visualization,Halo Visualization,Image Contours,Crop Visualization,Absolute Static Crop,Camera Focus,Image Blur,Trace Visualization,Circle Visualization,Buffer,Image Preprocessing,Background Color Visualization,Dot Visualization,Clip Comparison,Polygon Zone Visualization,Size Measurement,Florence-2 Model,Classification Label Visualization,Bounding Box Visualization,Corner Visualization,Llama 3.2 Vision,Image Slicer,Florence-2 Model,Dynamic Crop,Reference Path Visualization,Label Visualization,Mask Visualization,Stitch Images,Triangle Visualization,Stability AI Image Generation,Image Threshold,Line Counter Visualization,Dynamic Zone,Keypoint Visualization,Color Visualization,Blur Visualization,Anthropic Claude,Image Convert Grayscale,Polygon Visualization - outputs:
Clip Comparison,Perspective Correction,Cache Set,Object Detection Model,Path Deviation,OpenAI,Object Detection Model,Detections Consensus,VLM as Classifier,Keypoint Detection Model,Google Gemini,Grid Visualization,Ellipse Visualization,VLM as Detector,Halo Visualization,Crop Visualization,Trace Visualization,Circle Visualization,Buffer,Keypoint Detection Model,VLM as Detector,Dot Visualization,Clip Comparison,Polygon Zone Visualization,Size Measurement,Florence-2 Model,VLM as Classifier,Classification Label Visualization,Bounding Box Visualization,Florence-2 Model,Llama 3.2 Vision,Corner Visualization,Line Counter,Reference Path Visualization,Label Visualization,LMM For Classification,Mask Visualization,Webhook Sink,Triangle Visualization,Line Counter Visualization,Time in Zone,Color Visualization,Email Notification,Path Deviation,YOLO-World Model,Line Counter,Anthropic Claude,Instance Segmentation Model,Time in Zone,Instance Segmentation Model,Polygon Visualization
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"
]
}