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28 changes: 28 additions & 0 deletions CONTRIBUTING.md
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# How to Contribute

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202 changes: 202 additions & 0 deletions LICENSE
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59 changes: 59 additions & 0 deletions README.md
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# EdgeTPU simple camera examples

This repo contains a collection of examples that use camera streams
together with the EdgeTPU Python API.

## Installation

Before you start using the examples run
the ```download_models.sh``` script in order to download a selection of models.
These canned models will be downloaded and extracted to a new folder
```canned_models```.


Further requirements may be needed by the different camera libraries, check the
README file for the respective subfolder.

## Contents

* __Gstreamer__ Python examples using gstreamer to obtain camera images. These
examples work on Linux using a webcam, Raspberry Pi with
the Raspicam and on the Coral DevBoard using the Coral camera. For the
former two you will also need a Coral USB Accelerator to run the models.
* __Raspicam__ Python example using picamera. This is only intended for
Raspberry Pi and will require a Coral USB Accelerator.

## Canned models

For all the demos in this repository you can change the model and the labels
file by using the flags flags ```--model``` and
```--labels```. Be sure to use the models labeled _edgetpu, as those are
compiled for the accelerator - otherwise the model will run on the CPU and
be much slower.

For classification you need to select one of the classification models
and its corresponding labels file:

```
inception_v1_224_quant_edgetpu.tflite, imagenet_labels.txt
inception_v2_224_quant_edgetpu.tflite, imagenet_labels.txt
inception_v3_299_quant_edgetpu.tflite, imagenet_labels.txt
inception_v4_299_quant_edgetpu.tflite, imagenet_labels.txt
mobilenet_v1_1.0_224_quant_edgetpu.tflite, imagenet_labels.txt
mobilenet_v2_1.0_224_quant_edgetpu.tflite, imagenet_labels.txt
mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflite, inat_bird_labels.txt
mobilenet_v2_1.0_224_inat_insect_quant_edgetpu.tflite, inat_insect_labels.txt
mobilenet_v2_1.0_224_inat_plant_quant_edgetpu.tflite, inat_plant_labels.txt
```

For detection you need to select one of the SSD detection models
and its corresponding labels file:

```
mobilenet_ssd_v1_coco_quant_postprocess_edgetpu.tflite, coco_labels.txt
mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite, coco_labels.txt
mobilenet_ssd_v2_face_quant_postprocess_edgetpu.tflite, coco_labels.txt
```


16 changes: 16 additions & 0 deletions download_models.sh
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#!/bin/sh
# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

wget http://storage.googleapis.com/cloud-iot-edge-pretrained-models/canned_models.tar.gz
33 changes: 33 additions & 0 deletions gstreamer/README.md
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This folder contains two examples using gstreamer to obtain camera images. These
examples work on Linux using a webcam, Raspberry Pi with
the Raspicam and on the Coral DevBoard using the Coral camera. For the
former two you will also need a Coral USB Accelerator to run the models.

## Installation

Make sure the gstreamer libraries are install. On the Coral DevBoard this isn't
necessary, but on Raspberry Pi or a general Linux system it will be.

```
sh install_requirements.sh
```


## Classification Demo

```
python3 classify.py
```

You can change the model and the labels file using flags ```--model``` and
```--labels```.
## Detection Demo (SSD models)

```
python3 detect.py
```

As before, you can change the model and the labels file using flags ```--model```
and ```--labels```.


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