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

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

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[instance_segmentation_prediction, keypoint_detection_prediction, classification_prediction, object_detection_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"
}