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:
Segment Anything 2 Model,Image Slicer,Stability AI Inpainting,Clip Comparison,Perspective Correction,Object Detection Model,Roboflow Custom Metadata,Object Detection Model,SIFT Comparison,Detection Offset,Grid Visualization,Ellipse Visualization,SIFT,VLM as Detector,CogVLM,Image Contours,Multi-Label Classification Model,OpenAI,Absolute Static Crop,Camera Focus,Trace Visualization,Multi-Label Classification Model,VLM as Detector,Dot Visualization,Google Vision OCR,Identify Changes,Polygon Zone Visualization,Gaze Detection,Roboflow Dataset Upload,VLM as Classifier,Identify Outliers,Classification Label Visualization,Corner Visualization,Byte Tracker,Llama 3.2 Vision,Dynamic Crop,Reference Path Visualization,Label Visualization,Detections Stabilizer,Mask Visualization,Triangle Visualization,Line Counter Visualization,Template Matching,Dynamic Zone,Detections Transformation,Time in Zone,Model Monitoring Inference Aggregator,Blur Visualization,Line Counter,Anthropic Claude,Instance Segmentation Model,Webhook Sink,SIFT Comparison,Time in Zone,Instance Segmentation Model,Cosine Similarity,Slack Notification,Detections Filter,Stitch OCR Detections,Pixelate Visualization,Path Deviation,OpenAI,Relative Static Crop,Detections Consensus,Twilio SMS Notification,VLM as Classifier,Keypoint Detection Model,Roboflow Dataset Upload,Google Gemini,Model Comparison Visualization,Halo Visualization,JSON Parser,Crop Visualization,Byte Tracker,Image Blur,Circle Visualization,Velocity,Keypoint Detection Model,Image Preprocessing,Background Color Visualization,Bounding Rectangle,Florence-2 Model,Single-Label Classification Model,Bounding Box Visualization,Byte Tracker,Florence-2 Model,Image Slicer,Local File Sink,LMM For Classification,Stitch Images,Stability AI Image Generation,Image Threshold,Detections Stitch,OCR Model,LMM,Keypoint Visualization,Email Notification,Color Visualization,Path Deviation,Single-Label Classification Model,YOLO-World Model,CSV Formatter,Image Convert Grayscale,Detections Classes Replacement,Polygon Visualization - outputs:
Segment Anything 2 Model,Cache Get,Stability AI Inpainting,Clip Comparison,Perspective Correction,Cache Set,Object Detection Model,Roboflow Custom Metadata,Object Detection Model,SIFT Comparison,CogVLM,Ellipse Visualization,Multi-Label Classification Model,OpenAI,Trace Visualization,CLIP Embedding Model,Multi-Label Classification Model,Dot Visualization,Google Vision OCR,Roboflow Dataset Upload,Polygon Zone Visualization,Gaze Detection,Classification Label Visualization,Corner Visualization,Llama 3.2 Vision,Line Counter,Reference Path Visualization,Dynamic Crop,Label Visualization,Mask Visualization,Triangle Visualization,Template Matching,Line Counter Visualization,Model Monitoring Inference Aggregator,Time in Zone,Blur Visualization,Line Counter,Anthropic Claude,Instance Segmentation Model,Webhook Sink,Time in Zone,Instance Segmentation Model,Slack Notification,Pixelate Visualization,Path Deviation,OpenAI,Detections Consensus,Twilio SMS Notification,Keypoint Detection Model,Roboflow Dataset Upload,Google Gemini,Model Comparison Visualization,Halo Visualization,Crop Visualization,Image Blur,Distance Measurement,Circle Visualization,Keypoint Detection Model,Image Preprocessing,Background Color Visualization,Pixel Color Count,Size Measurement,Florence-2 Model,Single-Label Classification Model,Bounding Box Visualization,Florence-2 Model,Local File Sink,LMM For Classification,Stability AI Image Generation,Image Threshold,Detections Stitch,LMM,Keypoint Visualization,Email Notification,Color Visualization,Path Deviation,Single-Label Classification Model,YOLO-World Model,Polygon Visualization
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,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(string): 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
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:
Segment Anything 2 Model,Image Slicer,Stability AI Inpainting,Clip Comparison,Perspective Correction,Object Detection Model,Roboflow Custom Metadata,Object Detection Model,SIFT Comparison,Detection Offset,Grid Visualization,Ellipse Visualization,SIFT,VLM as Detector,CogVLM,Image Contours,Multi-Label Classification Model,OpenAI,Absolute Static Crop,Camera Focus,Trace Visualization,Multi-Label Classification Model,VLM as Detector,Dot Visualization,Google Vision OCR,Identify Outliers,Polygon Zone Visualization,Gaze Detection,Roboflow Dataset Upload,VLM as Classifier,Identify Changes,Classification Label Visualization,Corner Visualization,Byte Tracker,Llama 3.2 Vision,Dynamic Crop,Reference Path Visualization,Label Visualization,Detections Stabilizer,Mask Visualization,Triangle Visualization,Line Counter Visualization,Template Matching,Dynamic Zone,Detections Transformation,Time in Zone,Model Monitoring Inference Aggregator,Blur Visualization,Line Counter,Anthropic Claude,Instance Segmentation Model,Webhook Sink,SIFT Comparison,Time in Zone,Instance Segmentation Model,Slack Notification,Detections Filter,Stitch OCR Detections,Pixelate Visualization,Path Deviation,OpenAI,Relative Static Crop,Detections Consensus,Twilio SMS Notification,VLM as Classifier,Keypoint Detection Model,Roboflow Dataset Upload,Google Gemini,Model Comparison Visualization,Halo Visualization,JSON Parser,Crop Visualization,Byte Tracker,Image Blur,Circle Visualization,Velocity,Keypoint Detection Model,Image Preprocessing,Background Color Visualization,Bounding Rectangle,Florence-2 Model,Single-Label Classification Model,Bounding Box Visualization,Byte Tracker,Florence-2 Model,Image Slicer,Local File Sink,LMM For Classification,Stitch Images,Stability AI Image Generation,Image Threshold,Detections Stitch,OCR Model,LMM,Keypoint Visualization,Email Notification,Color Visualization,Path Deviation,Single-Label Classification Model,YOLO-World Model,CSV Formatter,Image Convert Grayscale,Detections Classes Replacement,Polygon Visualization - outputs:
Segment Anything 2 Model,Cache Get,Stability AI Inpainting,Clip Comparison,Perspective Correction,Cache Set,Object Detection Model,Roboflow Custom Metadata,Object Detection Model,SIFT Comparison,CogVLM,Ellipse Visualization,Multi-Label Classification Model,OpenAI,Trace Visualization,CLIP Embedding Model,Multi-Label Classification Model,Dot Visualization,Google Vision OCR,Roboflow Dataset Upload,Polygon Zone Visualization,Gaze Detection,Classification Label Visualization,Corner Visualization,Llama 3.2 Vision,Line Counter,Reference Path Visualization,Dynamic Crop,Label Visualization,Mask Visualization,Triangle Visualization,Template Matching,Line Counter Visualization,Model Monitoring Inference Aggregator,Time in Zone,Blur Visualization,Line Counter,Anthropic Claude,Instance Segmentation Model,Webhook Sink,Time in Zone,Instance Segmentation Model,Slack Notification,Pixelate Visualization,Path Deviation,OpenAI,Detections Consensus,Twilio SMS Notification,Keypoint Detection Model,Roboflow Dataset Upload,Google Gemini,Model Comparison Visualization,Halo Visualization,Crop Visualization,Image Blur,Distance Measurement,Circle Visualization,Keypoint Detection Model,Image Preprocessing,Background Color Visualization,Pixel Color Count,Size Measurement,Florence-2 Model,Single-Label Classification Model,Bounding Box Visualization,Florence-2 Model,Local File Sink,LMM For Classification,Stability AI Image Generation,Image Threshold,Detections Stitch,LMM,Keypoint Visualization,Email Notification,Color Visualization,Path Deviation,Single-Label Classification Model,YOLO-World Model,Polygon Visualization
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,object_detection_prediction,classification_prediction]): Model predictions to be uploaded..target_project(roboflow_project): Roboflow project where data will be saved..registration_tags(string): 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
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"
}