Dynamic Crop¶

Version v1¶

Create dynamic crops from an image based on detections from detections-based model.

This is useful when placed after an ObjectDetection block as part of a multi-stage workflow. For example, you could use an ObjectDetection block to detect objects, then the DynamicCropBlock block to crop objects, then an OCR block to run character recognition on each of the individual cropped regions.

In addition, for instance segmentation predictions (which provide segmentation mask for each bounding box) it is possible to remove background in the crops, outside of detected instances. To enable that functionality, set mask_opacity to positive value and optionally tune background_color.

Type identifier¶

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

Properties¶

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections¶

Check what blocks you can connect to Dynamic Crop in version v1.

• inputs: Color Visualization, Detections Filter, Detections Consensus, Image Contours, Path deviation, Image Preprocessing, Mask Visualization, Dot Visualization, Corner Visualization, Model Comparison Visualization, Image Slicer, Byte Tracker, Detection Offset, Keypoint Detection Model, Image Blur, Label Visualization, Time in zone, Relative Static Crop, Polygon Visualization, Camera Focus, Detections Classes Replacement, Dynamic Crop, YOLO-World Model, Halo Visualization, Segment Anything 2 Model, Crop Visualization, Image Threshold, SIFT, Google Vision OCR, Circle Visualization, SIFT Comparison, VLM as Detector, Path deviation, Byte Tracker, Object Detection Model, Stability AI Inpainting, Image Convert Grayscale, Line Counter Visualization, Absolute Static Crop, Background Color Visualization, Perspective Correction, Detections Transformation, Detections Stitch, Dominant Color, Bounding Box Visualization, Polygon Zone Visualization, Template Matching, Ellipse Visualization, Pixelate Visualization, Time in zone, Triangle Visualization, Instance Segmentation Model, Bounding Rectangle, Stitch Images, Blur Visualization
• outputs: Color Visualization, Image Contours, Image Preprocessing, Mask Visualization, Dot Visualization, Corner Visualization, Model Comparison Visualization, Image Slicer, Keypoint Detection Model, Image Blur, OCR Model, Label Visualization, Time in zone, Relative Static Crop, Florence-2 Model, Camera Focus, Clip Comparison, Polygon Visualization, Image Convert Grayscale, Dynamic Crop, YOLO-World Model, Halo Visualization, LMM For Classification, Segment Anything 2 Model, Crop Visualization, Image Threshold, Multi-Label Classification Model, QR Code Detection, Google Vision OCR, SIFT, Clip Comparison, LMM, Roboflow Dataset Upload, Barcode Detection, OpenAI, Circle Visualization, SIFT Comparison, VLM as Detector, Google Gemini, CogVLM, Anthropic Claude, Object Detection Model, Pixel Color Count, Stability AI Inpainting, OpenAI, Absolute Static Crop, Background Color Visualization, Perspective Correction, Detections Stitch, Line Counter Visualization, Dominant Color, Template Matching, Bounding Box Visualization, Polygon Zone Visualization, Ellipse Visualization, Pixelate Visualization, Triangle Visualization, Roboflow Dataset Upload, Instance Segmentation Model, Single-Label Classification Model, VLM as Classifier, Stitch Images, Blur Visualization

The available connections depend on its binding kinds. Check what binding kinds Dynamic Crop in version v1 has.

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/dynamic_crop@v1",
    "images": "$inputs.image",
    "predictions": "$steps.my_object_detection_model.predictions",
    "mask_opacity": "<block_does_not_provide_example>",
    "background_color": "#431112"
}