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Merge pull request #972 from roboflow/fix/perspective_correction-inpu…
…t-accept-output-of-dynamic-zones Fix/perspective correction input accept output of dynamic zones
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.../integration_tests/execution/test_workflow_with_dynamic_zone_and_perspective_converter.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,165 @@ | ||
| import numpy as np | ||
|
|
||
| from inference.core.env import WORKFLOWS_MAX_CONCURRENT_STEPS | ||
| from inference.core.managers.base import ModelManager | ||
| from inference.core.workflows.core_steps.common.entities import StepExecutionMode | ||
| from inference.core.workflows.core_steps.transformations.perspective_correction.v1 import ( | ||
| OUTPUT_DETECTIONS_KEY as PERSPECTIVE_CORRECTION_OUTPUT_DETECTIONS_KEY, | ||
| OUTPUT_IMAGE_KEY as PERSPECTIVE_CORRECTION_OUTPUT_IMAGE_KEY, | ||
| ) | ||
| from inference.core.workflows.core_steps.transformations.dynamic_zones.v1 import ( | ||
| OUTPUT_KEY as DYNAMIC_ZONES_OUTPUT_KEY, | ||
| ) | ||
| from inference.core.workflows.execution_engine.core import ExecutionEngine | ||
| from tests.workflows.integration_tests.execution.workflows_gallery_collector.decorators import ( | ||
| add_to_workflows_gallery, | ||
| ) | ||
|
|
||
| WORKFLOW_DYNAMIC_ZONE_AND_PERSPECTIVE_CONVERTER = { | ||
| "version": "1.0", | ||
| "inputs": [{"type": "InferenceImage", "name": "image"}], | ||
| "steps": [ | ||
| { | ||
| "type": "roboflow_core/roboflow_instance_segmentation_model@v2", | ||
| "name": "model", | ||
| "images": "$inputs.image", | ||
| "model_id": "yolov8n-seg-640", | ||
| }, | ||
| { | ||
| "type": "roboflow_core/detections_filter@v1", | ||
| "name": "detections_filter", | ||
| "predictions": "$steps.model.predictions", | ||
| "operations": [ | ||
| { | ||
| "type": "DetectionsFilter", | ||
| "filter_operation": { | ||
| "type": "StatementGroup", | ||
| "operator": "and", | ||
| "statements": [ | ||
| { | ||
| "type": "BinaryStatement", | ||
| "negate": False, | ||
| "left_operand": { | ||
| "type": "DynamicOperand", | ||
| "operand_name": "_", | ||
| "operations": [ | ||
| { | ||
| "type": "ExtractDetectionProperty", | ||
| "property_name": "class_name", | ||
| } | ||
| ], | ||
| }, | ||
| "comparator": {"type": "in (Sequence)"}, | ||
| "right_operand": { | ||
| "type": "StaticOperand", | ||
| "value": ["banana"], | ||
| }, | ||
| } | ||
| ], | ||
| }, | ||
| } | ||
| ], | ||
| "operations_parameters": {}, | ||
| }, | ||
| { | ||
| "type": "roboflow_core/dynamic_zone@v1", | ||
| "name": "dynamic_zone", | ||
| "predictions": "$steps.detections_filter.predictions", | ||
| "required_number_of_vertices": 4, | ||
| }, | ||
| { | ||
| "type": "roboflow_core/perspective_correction@v1", | ||
| "name": "perspective_correction", | ||
| "images": "$inputs.image", | ||
| "perspective_polygons": f"$steps.dynamic_zone.{DYNAMIC_ZONES_OUTPUT_KEY}", | ||
| "predictions": "$steps.model.predictions", | ||
| "warp_image": True, | ||
| "extend_perspective_polygon_by_detections_anchor": "BOTTOM_CENTER", | ||
| }, | ||
| { | ||
| "type": "roboflow_core/polygon_visualization@v1", | ||
| "name": "perspective_visualization", | ||
| "image": f"$steps.perspective_correction.{PERSPECTIVE_CORRECTION_OUTPUT_IMAGE_KEY}", | ||
| "predictions": f"$steps.perspective_correction.{PERSPECTIVE_CORRECTION_OUTPUT_DETECTIONS_KEY}", | ||
| }, | ||
| { | ||
| "type": "roboflow_core/polygon_visualization@v1", | ||
| "name": "polygon_visualization", | ||
| "image": "$inputs.image", | ||
| "predictions": "$steps.model.predictions", | ||
| }, | ||
| ], | ||
| "outputs": [ | ||
| { | ||
| "type": "JsonField", | ||
| "name": "polygons_visualization", | ||
| "coordinates_system": "own", | ||
| "selector": "$steps.polygon_visualization.image", | ||
| }, | ||
| { | ||
| "type": "JsonField", | ||
| "name": "perspective_visualization", | ||
| "coordinates_system": "own", | ||
| "selector": "$steps.perspective_visualization.image", | ||
| }, | ||
| { | ||
| "type": "JsonField", | ||
| "name": "perspective_correction_outputs", | ||
| "coordinates_system": "own", | ||
| "selector": "$steps.perspective_correction.*", | ||
| }, | ||
| { | ||
| "type": "JsonField", | ||
| "name": "dynamic_zones", | ||
| "coordinates_system": "own", | ||
| "selector": "$steps.dynamic_zone.zones", | ||
| }, | ||
| ], | ||
| } | ||
|
|
||
|
|
||
| @add_to_workflows_gallery( | ||
| category="Workflows with classical Computer Vision methods", | ||
| use_case_title="Workflow with dynamic zone and perspective converter", | ||
| use_case_description=""" | ||
| In this example dynamic zone with 4 vertices is calculated from detected segmentations. | ||
| Perspective correction is applied to the input image as well as to detected segmentations based on this zone. | ||
| """, | ||
| workflow_definition=WORKFLOW_DYNAMIC_ZONE_AND_PERSPECTIVE_CONVERTER, | ||
| workflow_name_in_app="dynamic_zone_and_perspective_converter", | ||
| ) | ||
| def test_workflow_with_classical_pattern_matching( | ||
| model_manager: ModelManager, | ||
| fruit_image: np.ndarray, | ||
| ) -> None: | ||
| # given | ||
| workflow_init_parameters = { | ||
| "workflows_core.model_manager": model_manager, | ||
| "workflows_core.api_key": None, | ||
| "workflows_core.step_execution_mode": StepExecutionMode.LOCAL, | ||
| } | ||
| execution_engine = ExecutionEngine.init( | ||
| workflow_definition=WORKFLOW_DYNAMIC_ZONE_AND_PERSPECTIVE_CONVERTER, | ||
| init_parameters=workflow_init_parameters, | ||
| max_concurrent_steps=WORKFLOWS_MAX_CONCURRENT_STEPS, | ||
| ) | ||
|
|
||
| # when | ||
| result = execution_engine.run( | ||
| runtime_parameters={ | ||
| "image": fruit_image, | ||
| } | ||
| ) | ||
|
|
||
| # then | ||
| assert isinstance(result, list), "Expected result to be list" | ||
| assert len(result) == 1, "One set of images provided, so one output expected" | ||
| assert set(result[0].keys()) == { | ||
| "dynamic_zones", | ||
| "polygons_visualization", | ||
| "perspective_correction_outputs", | ||
| "perspective_visualization", | ||
| }, "Expected all declared outputs to be delivered" | ||
| assert ( | ||
| len(result[0]["perspective_correction_outputs"]["corrected_coordinates"]) == 6 | ||
| ), "Expected 6 detections in corrected coordinates" |