TensorFlight automatically detects and counts various types of objects from aerial imagery. We started with detecting trees, but we are also partially supporting:

• Animals
• Cars
• Parking spaces

As an ilustrative example, here is a result of our algorithm imported to QGIS:

For instructions how to replicate this view see the section Analyze Shapefile in QGIS.

What’s more, we are also supporting advanced analysis within a category. We are already distinguishing between healthy and dead trees. We are working on more in-depth classification algorithms, for example classifying tree type and age.

If an category you are interested in is not in the list, we can adapt to any new object type within a few weeks. Please contact us at support@tensorflight.com.

Before we can adapt an algorithm to a new categories we need to access reference images. The best way is to use our app, even if you category is not in the list and send us a plan id like described in the Ask for TensorFlight team’s help section.

You can also open the app store directly at https://www.dronedeploy.com/app2/applications.

Click the map you would like to process.

Expand the TensorFlight section by clicking the triangle button and click “Analyze the map”.

You may only interested in performing analysis on part of the map. In order to do so, select an option “Parts of the map” and pick annotations you are interested in.

You firstly need to create an Area annotation by clicking the “Area” button. We recommend adding a distinctive color or title for your new annotation.

Secondly, you need to pick annotations you are interested in and click the “Confirm” button.

Don’t worry, you will be able to change the selected area without restarting the whole processing.

Wait until processing finishes:

It should be finished within minutes for majority of maps, but can take a few hours for very big maps.

Summary gives you a total count of objects in the selected area.

Detailed view lets you explore the view of the map with annotation for each object:

Shapefile lets you export results of the analysis to GIS software. Officially supported options are QGIS or ArcGIS.

For GIS experts – Shapefile consists of a layer named “TensorFlight” in EPSG 4326 projection with a polygon feature per object with a string field “type” representing object type – e.g. “Healthy tree” or “Parked vehicle” as seen in the examples in following sections.

1. Install QGIS.
2. Unzip the exported zip and import the .shp file to QGIS like in the tutorial at https://www.youtube.com/watch?v=ehwoRkT-V7k.
3. Select categorized layer style as described in http://www.qgistutorials.com/en/docs/basic_vector_styling.html. Optionally change the layer tranparency in the style section.
4. Right click the layer in the “Layers Panel” section and tick “Show feature count”.
5. Optionally load your map as background in QGIS. Remember to use EPSG 4326 projection during the export.

You should results like this:

In order to upload shapefile to ArcGis online:

1. Add -> Add Layer from File -> Choose File -> Select zip file
2. Select “Keep original features”
3. Click “Import layer”
4. Select the drawing style “Types”
5. Optionally select the Basemap

You should see results like this:

If we recently updated our app, your browser may still be using old version of our app. Problem should In order to force update to the latest version you may need to clear your browser cache. instructions for chrome, instructions for firefox, intructions for Microsoft Edge.

Our current app loads all your imagery into the browser. Your computer may not have enough ram to process it. If you are dealing with very big maps, recommended way to analyze results is to export the shapefile and analyze results in QGIS or ArcGIS.

We aim to process majority of requests within minutes and all reqests within 24 hours. We are sorry if you have been waiting longer. We are likely already working on solving your problem, but you may also contact our support, as decribed in the Ask for TensorFlight team’s help section.