Inference using DeepForest model
This example uses a raster file from the original DeepForest Respository. For additional information about the model performance please refer to the repository.
DeepForest is an Object Detection Model. That means it will generate a bounding box of each detected object. That means that for this case 2 vector layers can be generated using TreeEyed:
Direct result:
Bounding Boxes vector layer
Derived results:
Centroids vector layer
Input
For this example we will use this image of a silvopastoral system.
Feature |
Value |
Unit |
|---|---|---|
Spatial resolution |
0.5 |
m |
Width |
922 |
px |
Height |
460 |
px |
The raster file is available to download here.
Configuration
Input
Select the appropiate Input layer from the dropdown menu.
For Extent select Layer extent.
Output
Select the appropiate Output directory and Output name.
Processing
- Go to the Inference tab
Select DeepForest model from the dropdown menu
Select the desired Result types, the direct result type for this model are Bounding Boxes
Press Process to start the inference process
Results
The resulting added layers depend on the selected Result types
Direct result:
Processing Result |
Result Type |
Result |
|---|---|---|
RASTER LAYERS |
||
Derived Result |
Binary |
NOT AVAILABLE FOR THIS MODEL |
Derived result |
Grayscale |
NOT AVAILABLE FOR THIS MODEL |
VECTOR LAYERS |
||
Derived result |
Polygons |
NOT AVAILABLE FOR THIS MODEL |
Direct result |
Bounding Boxes |
|
Derived result |
Centroids |
|