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53 lines
2.0 KiB
53 lines
2.0 KiB
3 years ago
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# Classify an image using an IoT Edge based image classifier - Wio Terminal
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In this part of the lesson, you will use the Image Classifier running on the IoT Edge device.
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## Use the IoT Edge classifier
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The IoT device can be re-directed to use the IoT Edge image classifier. The URL for the Image Classifier is `http://<IP address or name>/image`, replacing `<IP address or name>` with the IP address or host name of the computer running IoT Edge.
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### Task - use the IoT Edge classifier
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1. Open the `fruit-quality-detector` app project if it's not already open.
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1. The image classifier is running as a REST API using HTTP, not HTTPS, so the call needs to use a WiFi client that works with HTTP calls only. This means the certificate is not needed. Delete the `CERTIFICATE` from the `config.h` file.
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1. The prediction URL in the `config.h` file needs to be updated to the new URL. You can also delete the `PREDICTION_KEY` as this is not needed.
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```cpp
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const char *PREDICTION_URL = "<URL>";
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```
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Replace `<URL>` with the URL for your classifier.
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1. In `main.cpp`, change the include directive for the WiFi Client Secure to import the standard HTTP version:
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```cpp
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#include <WiFiClient.h>
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```
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1. Change the declaration of `WiFiClient` to be the HTTP version:
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```cpp
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WiFiClient client;
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```
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1. Select the line that sets the certificate on the WiFi client. Remove the line `client.setCACert(CERTIFICATE);` from the `connectWiFi` function.
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1. In the `classifyImage` function, remove the `httpClient.addHeader("Prediction-Key", PREDICTION_KEY);` line that sets the prediction key in the header.
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1. Upload and run your code. Point the camera at some fruit and press the C button. You will see the output in the serial monitor:
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```output
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Connecting to WiFi..
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Connected!
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Image captured
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Image read to buffer with length 8200
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ripe: 56.84%
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unripe: 43.16%
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```
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> 💁 You can find this code in the [code-classify/wio-terminal](code-classify/wio-terminal) folder.
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😀 Your fruit quality classifier program was a success!
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