We are excited to introduce a dedicated custom transformer for PDAL (Point Data Abstraction Library) within FME: PDALPipelineApplier.
📹 Check out the video demonstrating how the transformer is used to cluster a point cloud to help fix its classification!
🔗 Learn More and Download : https://hub.safe.com/publishers/antoine/transformers/pdalpipelineapplier
Why PDAL?
PDAL is a powerful PointCloud library widely used in the industry. Available through Conda, it is well-suited for low-code users thanks to its JSON pipelines.
✨ PDAL complements FME excellently, especially for segment-level operations:
✔️ Normal Computation: Essential in point cloud processing.
✔️ Segmentation: Offers multiple clustering algorithms.
✔️ Ground Classification: Crucial for deriving all other classes in a point cloud.
✔️ Outlier Detection: Identifies and removes anomalies.
Key Benefits
✅ Seamless Integration: Easily incorporate PDAL into FME.
✅ User-Friendly: PDAL’s JSON-based pipeline fits perfectly with FME’s low-code environment.
Enhanced Experience with FME
🔍 Live Visualization: Instantly see your data and results as you build your workflows.
🔧 Fun and Productivity: FME’s Visual Pipeline Building enhances your experience.
🌍 Reach: FME takes interoperability to the next level, adding formats and multiple transformers to combine your point cloud with raster and vector-based formats.
🛠️Requirements
This custom transformer requires a Conda environment for proper dependency management.
🎮Get Started
Explore the new capabilities of PDAL within FME and enhance your point cloud processing tasks today.
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