Roboflow Dataset Upload

v2

Class: RoboflowDatasetUploadBlockV2 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v2.RoboflowDatasetUploadBlockV2

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

Block let users save their images and predictions into Roboflow Dataset. Persisting data from production environments helps iteratively building more robust models.

Block provides configuration options to decide how data should be stored and what are the limits to be applied. We advice using this block in combination with rate limiter blocks to effectively collect data that the model struggle with.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
target_project	str	Roboflow project where data will be saved..	✅
data_percentage	float	Percent of data that will be saved (0.0 to 100.0)..	✅
minutely_usage_limit	int	Maximum number of image uploads allowed per minute..	❌
hourly_usage_limit	int	Maximum number of image uploads allowed per hour..	❌
daily_usage_limit	int	Maximum number of image uploads allowed per day..	❌
usage_quota_name	str	A unique identifier for tracking usage quotas (minutely, hourly, daily limits)..	❌
max_image_size	Tuple[int, int]	Maximum size of the image to be saved. Bigger images will be downsized preserving aspect ratio..	❌
compression_level	int	Compression level for the registered image..	❌
registration_tags	List[str]	Tags to be attached to the registered image..	✅
persist_predictions	bool	Boolean flag to specify if model predictions should be saved along with the image..	✅
disable_sink	bool	Boolean flag to disable block execution..	✅
fire_and_forget	bool	Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling..	✅
labeling_batch_prefix	str	Target batch name for the registered image..	✅
labeling_batches_recreation_frequency	str	Frequency in which new labeling batches are created for uploaded images..	❌

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 Roboflow Dataset Upload in version v2.

• inputs: QR Code Generator, Image Convert Grayscale, Google Gemini, Velocity, SIFT Comparison, Blur Visualization, Detection Offset, SIFT, Bounding Box Visualization, Stability AI Outpainting, Trace Visualization, Instance Segmentation Model, Ellipse Visualization, Model Comparison Visualization, Dimension Collapse, OpenAI, Triangle Visualization, SAM 3, Byte Tracker, Stability AI Image Generation, Path Deviation, VLM as Detector, Florence-2 Model, Single-Label Classification Model, Email Notification, Google Gemini, Segment Anything 2 Model, Camera Focus, VLM as Classifier, Corner Visualization, Color Visualization, Twilio SMS/MMS Notification, Multi-Label Classification Model, Image Slicer, OpenAI, Line Counter, Buffer, Detections Transformation, SAM 3, Dot Visualization, Roboflow Custom Metadata, Image Threshold, Model Monitoring Inference Aggregator, Classification Label Visualization, OCR Model, Time in Zone, Byte Tracker, Roboflow Dataset Upload, Mask Visualization, Detections List Roll-Up, Pixelate Visualization, Keypoint Detection Model, Detections Consensus, Size Measurement, Webhook Sink, Stability AI Inpainting, Template Matching, Line Counter Visualization, Crop Visualization, OpenAI, Llama 3.2 Vision, Icon Visualization, Clip Comparison, Time in Zone, Background Subtraction, LMM For Classification, SAM 3, Object Detection Model, CogVLM, Roboflow Dataset Upload, Overlap Filter, Detections Stitch, Detections Combine, Seg Preview, Byte Tracker, YOLO-World Model, Dynamic Crop, Identify Changes, Camera Focus, Slack Notification, Keypoint Visualization, Polygon Visualization, Anthropic Claude, Local File Sink, Polygon Zone Visualization, Halo Visualization, LMM, Time in Zone, Circle Visualization, Detections Stabilizer, Google Vision OCR, Motion Detection, Clip Comparison, Cosine Similarity, Detections Classes Replacement, Anthropic Claude, Detections Filter, Object Detection Model, Instance Segmentation Model, Perspective Correction, CSV Formatter, Reference Path Visualization, Stitch OCR Detections, Camera Calibration, Image Blur, VLM as Detector, Morphological Transformation, Label Visualization, Background Color Visualization, Keypoint Detection Model, Path Deviation, Dynamic Zone, Absolute Static Crop, PTZ Tracking (ONVIF).md), Moondream2, Grid Visualization, Contrast Equalization, Image Preprocessing, Google Gemini, Relative Static Crop, OpenAI, Image Contours, Stitch Images, JSON Parser, Bounding Rectangle, SIFT Comparison, Gaze Detection, Identify Outliers, Depth Estimation, Twilio SMS Notification, Single-Label Classification Model, VLM as Classifier, Florence-2 Model, Detections Merge, Multi-Label Classification Model, EasyOCR, Image Slicer, Email Notification
• outputs: QR Code Generator, Google Gemini, Blur Visualization, Bounding Box Visualization, Stability AI Outpainting, Trace Visualization, Instance Segmentation Model, Pixel Color Count, Ellipse Visualization, Model Comparison Visualization, OpenAI, Triangle Visualization, SAM 3, Distance Measurement, Stability AI Image Generation, Path Deviation, CLIP Embedding Model, Florence-2 Model, Single-Label Classification Model, Email Notification, Google Gemini, Twilio SMS/MMS Notification, Color Visualization, Corner Visualization, Multi-Label Classification Model, OpenAI, Line Counter, SAM 3, Roboflow Custom Metadata, Dot Visualization, Image Threshold, Model Monitoring Inference Aggregator, Time in Zone, Classification Label Visualization, Roboflow Dataset Upload, Mask Visualization, Pixelate Visualization, Line Counter, Keypoint Detection Model, Detections Consensus, Size Measurement, Webhook Sink, Stability AI Inpainting, Template Matching, Line Counter Visualization, Crop Visualization, OpenAI, Llama 3.2 Vision, Icon Visualization, Time in Zone, LMM For Classification, SAM 3, Object Detection Model, CogVLM, Roboflow Dataset Upload, Cache Get, Detections Stitch, Seg Preview, YOLO-World Model, Dynamic Crop, Slack Notification, Keypoint Visualization, Polygon Visualization, Cache Set, Anthropic Claude, Local File Sink, Polygon Zone Visualization, Halo Visualization, LMM, Time in Zone, Circle Visualization, Google Vision OCR, Motion Detection, Clip Comparison, Detections Classes Replacement, Anthropic Claude, Object Detection Model, Instance Segmentation Model, Perspective Correction, Perception Encoder Embedding Model, Reference Path Visualization, Stitch OCR Detections, Image Blur, Morphological Transformation, Label Visualization, Background Color Visualization, Keypoint Detection Model, Path Deviation, Dynamic Zone, PTZ Tracking (ONVIF).md), Moondream2, Image Preprocessing, Contrast Equalization, Google Gemini, OpenAI, SIFT Comparison, Gaze Detection, Depth Estimation, Twilio SMS Notification, Single-Label Classification Model, Florence-2 Model, Multi-Label Classification Model, Segment Anything 2 Model, Email Notification

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Roboflow Dataset Upload in version v2 has.

Bindings

• input

  • images (image): The image to upload..
  • target_project (roboflow_project): Roboflow project where data will be saved..
  • predictions (Union[keypoint_detection_prediction, instance_segmentation_prediction, object_detection_prediction, classification_prediction]): Model predictions to be uploaded..
  • data_percentage (float): Percent of data that will be saved (0.0 to 100.0)..
  • registration_tags (Union[string, list_of_values]): Tags to be attached to the registered image..
  • persist_predictions (boolean): Boolean flag to specify if model predictions should be saved along with the image..
  • disable_sink (boolean): Boolean flag to disable block execution..
  • fire_and_forget (boolean): Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling..
  • labeling_batch_prefix (string): Target batch name for the registered image..

• output

  • error_status (boolean): Boolean flag.
  • message (string): String value.

Example JSON definition of step Roboflow Dataset Upload in version v2

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/roboflow_dataset_upload@v2",
    "images": "$inputs.image",
    "target_project": "my_dataset",
    "predictions": "$steps.object_detection_model.predictions",
    "data_percentage": true,
    "minutely_usage_limit": 10,
    "hourly_usage_limit": 10,
    "daily_usage_limit": 10,
    "usage_quota_name": "quota-for-data-sampling-1",
    "max_image_size": [
        1920,
        1080
    ],
    "compression_level": 95,
    "registration_tags": [
        "location-florida",
        "factory-name",
        "$inputs.dynamic_tag"
    ],
    "persist_predictions": true,
    "disable_sink": true,
    "fire_and_forget": "<block_does_not_provide_example>",
    "labeling_batch_prefix": "my_labeling_batch_name",
    "labeling_batches_recreation_frequency": "never"
}

v1

Class: RoboflowDatasetUploadBlockV1 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.RoboflowDatasetUploadBlockV1

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

Block let users save their images and predictions into Roboflow Dataset. Persisting data from production environments helps iteratively building more robust models.

Block provides configuration options to decide how data should be stored and what are the limits to be applied. We advice using this block in combination with rate limiter blocks to effectively collect data that the model struggle with.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
target_project	str	Roboflow project where data will be saved..	✅
minutely_usage_limit	int	Maximum number of image uploads allowed per minute..	❌
hourly_usage_limit	int	Maximum number of image uploads allowed per hour..	❌
daily_usage_limit	int	Maximum number of image uploads allowed per day..	❌
usage_quota_name	str	A unique identifier for tracking usage quotas (minutely, hourly, daily limits)..	❌
max_image_size	Tuple[int, int]	Maximum size of the image to be saved. Bigger images will be downsized preserving aspect ratio..	❌
compression_level	int	Compression level for the registered image..	❌
registration_tags	List[str]	Tags to be attached to the registered image..	✅
persist_predictions	bool	Boolean flag to specify if model predictions should be saved along with the image..	❌
disable_sink	bool	Boolean flag to disable block execution..	✅
fire_and_forget	bool	Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling..	✅
labeling_batch_prefix	str	Target batch name for the registered image..	✅
labeling_batches_recreation_frequency	str	Frequency in which new labeling batches are created for uploaded images..	❌

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 Roboflow Dataset Upload in version v1.

• inputs: QR Code Generator, Image Convert Grayscale, Google Gemini, Velocity, SIFT Comparison, Blur Visualization, Detection Offset, SIFT, Bounding Box Visualization, Stability AI Outpainting, Trace Visualization, Instance Segmentation Model, Ellipse Visualization, Model Comparison Visualization, Dimension Collapse, OpenAI, Triangle Visualization, SAM 3, Byte Tracker, Stability AI Image Generation, Path Deviation, VLM as Detector, Florence-2 Model, Single-Label Classification Model, Email Notification, Google Gemini, Segment Anything 2 Model, Camera Focus, VLM as Classifier, Corner Visualization, Color Visualization, Twilio SMS/MMS Notification, Multi-Label Classification Model, Image Slicer, OpenAI, Line Counter, Buffer, Detections Transformation, SAM 3, Dot Visualization, Roboflow Custom Metadata, Image Threshold, Model Monitoring Inference Aggregator, Classification Label Visualization, OCR Model, Time in Zone, Byte Tracker, Roboflow Dataset Upload, Mask Visualization, Detections List Roll-Up, Pixelate Visualization, Keypoint Detection Model, Detections Consensus, Size Measurement, Webhook Sink, Stability AI Inpainting, Template Matching, Line Counter Visualization, Crop Visualization, OpenAI, Llama 3.2 Vision, Icon Visualization, Clip Comparison, Time in Zone, Background Subtraction, LMM For Classification, SAM 3, Object Detection Model, CogVLM, Roboflow Dataset Upload, Overlap Filter, Detections Stitch, Detections Combine, Seg Preview, Byte Tracker, YOLO-World Model, Dynamic Crop, Identify Changes, Camera Focus, Slack Notification, Keypoint Visualization, Polygon Visualization, Anthropic Claude, Local File Sink, Polygon Zone Visualization, Halo Visualization, LMM, Time in Zone, Circle Visualization, Detections Stabilizer, Google Vision OCR, Motion Detection, Clip Comparison, Detections Classes Replacement, Anthropic Claude, Detections Filter, Object Detection Model, Instance Segmentation Model, Perspective Correction, CSV Formatter, Reference Path Visualization, Stitch OCR Detections, Camera Calibration, Image Blur, VLM as Detector, Morphological Transformation, Label Visualization, Background Color Visualization, Keypoint Detection Model, Path Deviation, Dynamic Zone, Absolute Static Crop, PTZ Tracking (ONVIF).md), Moondream2, Grid Visualization, Contrast Equalization, Image Preprocessing, Google Gemini, Relative Static Crop, OpenAI, Image Contours, Stitch Images, JSON Parser, Bounding Rectangle, SIFT Comparison, Gaze Detection, Identify Outliers, Depth Estimation, Twilio SMS Notification, Single-Label Classification Model, VLM as Classifier, Florence-2 Model, Detections Merge, Multi-Label Classification Model, EasyOCR, Image Slicer, Email Notification
• outputs: QR Code Generator, Google Gemini, Blur Visualization, Bounding Box Visualization, Stability AI Outpainting, Trace Visualization, Instance Segmentation Model, Pixel Color Count, Ellipse Visualization, Model Comparison Visualization, OpenAI, Triangle Visualization, SAM 3, Distance Measurement, Stability AI Image Generation, Path Deviation, CLIP Embedding Model, Florence-2 Model, Single-Label Classification Model, Email Notification, Google Gemini, Twilio SMS/MMS Notification, Color Visualization, Corner Visualization, Multi-Label Classification Model, OpenAI, Line Counter, SAM 3, Roboflow Custom Metadata, Dot Visualization, Image Threshold, Model Monitoring Inference Aggregator, Time in Zone, Classification Label Visualization, Roboflow Dataset Upload, Mask Visualization, Pixelate Visualization, Line Counter, Keypoint Detection Model, Detections Consensus, Size Measurement, Webhook Sink, Stability AI Inpainting, Template Matching, Line Counter Visualization, Crop Visualization, OpenAI, Llama 3.2 Vision, Icon Visualization, Time in Zone, LMM For Classification, SAM 3, Object Detection Model, CogVLM, Roboflow Dataset Upload, Cache Get, Detections Stitch, Seg Preview, YOLO-World Model, Dynamic Crop, Slack Notification, Keypoint Visualization, Polygon Visualization, Cache Set, Anthropic Claude, Local File Sink, Polygon Zone Visualization, Halo Visualization, LMM, Time in Zone, Circle Visualization, Google Vision OCR, Motion Detection, Clip Comparison, Detections Classes Replacement, Anthropic Claude, Object Detection Model, Instance Segmentation Model, Perspective Correction, Perception Encoder Embedding Model, Reference Path Visualization, Stitch OCR Detections, Image Blur, Morphological Transformation, Label Visualization, Background Color Visualization, Keypoint Detection Model, Path Deviation, Dynamic Zone, PTZ Tracking (ONVIF).md), Moondream2, Image Preprocessing, Contrast Equalization, Google Gemini, OpenAI, SIFT Comparison, Gaze Detection, Depth Estimation, Twilio SMS Notification, Single-Label Classification Model, Florence-2 Model, Multi-Label Classification Model, Segment Anything 2 Model, Email Notification

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Roboflow Dataset Upload in version v1 has.

Bindings

• input

  • image (image): Image to upload..
  • predictions (Union[keypoint_detection_prediction, instance_segmentation_prediction, object_detection_prediction, classification_prediction]): Model predictions to be uploaded..
  • target_project (roboflow_project): Roboflow project where data will be saved..
  • registration_tags (Union[string, list_of_values]): Tags to be attached to the registered image..
  • disable_sink (boolean): Boolean flag to disable block execution..
  • fire_and_forget (boolean): Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling..
  • labeling_batch_prefix (string): Target batch name for the registered image..

• output

  • error_status (boolean): Boolean flag.
  • message (string): String value.

Example JSON definition of step Roboflow Dataset Upload in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/roboflow_dataset_upload@v1",
    "image": "$inputs.image",
    "predictions": "$steps.object_detection_model.predictions",
    "target_project": "my_project",
    "minutely_usage_limit": 10,
    "hourly_usage_limit": 10,
    "daily_usage_limit": 10,
    "usage_quota_name": "quota-for-data-sampling-1",
    "max_image_size": [
        512,
        512
    ],
    "compression_level": 75,
    "registration_tags": [
        "location-florida",
        "factory-name",
        "$inputs.dynamic_tag"
    ],
    "persist_predictions": true,
    "disable_sink": true,
    "fire_and_forget": true,
    "labeling_batch_prefix": "my_labeling_batch_name",
    "labeling_batches_recreation_frequency": "never"
}