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PiperOrigin-RevId: 254856010
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MediaPipe Team
2019-06-24 16:19:49 -07:00
committed by jqtang
parent fcb23fd99d
commit 2aaf4693db
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mediapipe/docs/object_detection_desktop.md
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@@ -8,7 +8,14 @@ interested in running the same TensorfFlow Lite model on Android, please see the
[Object Detection on GPU on Android](object_detection_android_gpu.md) and
[Object Detection on CPU on Android](object_detection_android_cpu.md) examples.
### TensorFlow Model
We show the object detection demo with both TensorFlow model and TensorFlow Lite model:
- [TensorFlow Object Detection Demo](#tensorflow-object-detection-demo)
- [TensorFlow Lite Object Detection Demo](#tensorflow-lite-object-detection-demo)
Note: If MediaPipe depends on OpenCV 2, please see the [known issues with OpenCV 2](#known-issues-with-opencv-2) section.
### TensorFlow Object Detection Demo
To build and run the TensorFlow example on desktop, run:
@@ -40,7 +47,7 @@ $ bazel-bin/mediapipe/examples/desktop/object_detection/object_detection_tensorf
To visualize the graph as shown above, copy the text specification of the graph
below and paste it into
[MediaPipe Visualizer](https://mediapipe-viz.appspot.com).
[MediaPipe Visualizer](https://viz.mediapipe.dev).
```bash
# MediaPipe graph that performs object detection on desktop with TensorFlow
@@ -176,7 +183,7 @@ node {
}
```
### TensorFlow Lite Model
### TensorFlow Lite Object Detection Demo
To build and run the TensorFlow Lite example on desktop, run:
@@ -204,7 +211,7 @@ $ bazel-bin/mediapipe/examples/desktop/object_detection/object_detection_tflite
To visualize the graph as shown above, copy the text specification of the graph
below and paste it into
[MediaPipe Visualizer](https://mediapipe-viz.appspot.com).
[MediaPipe Visualizer](https://viz.mediapipe.dev).
```bash
# MediaPipe graph that performs object detection on desktop with TensorFlow Lite