https://github.com/muhammedbuyukkinaci/fruit-detector

Implementation of TensorFlow Object Detection API on fruit images.
https://github.com/muhammedbuyukkinaci/fruit-detector

Last synced: 6 months ago
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Implementation of TensorFlow Object Detection API on fruit images.

Host: GitHub
URL: https://github.com/muhammedbuyukkinaci/fruit-detector
Owner: MuhammedBuyukkinaci
Created: 2018-07-02T19:27:28.000Z (over 7 years ago)
Default Branch: master
Last Pushed: 2018-07-19T06:26:26.000Z (about 7 years ago)
Last Synced: 2025-03-30T18:43:57.139Z (7 months ago)
Language: Python
Homepage:
Size: 19.8 MB
Stars: 37
Watchers: 7
Forks: 15
Open Issues: 1
Metadata Files:
- Readme: README.md

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README

# Fruit-Detector
Implementation of [TensorFlow Object Detection API on Windows 10](https://www.youtube.com/watch?v=Rgpfk6eYxJA) with fruit images without Anaconda Distribution.

# Changes

No Anaconda Distribution. Use command prompt instead of Anaconda Prompt.

1)Don't use the below commands in 2d.

```conda create -n tensorflow1 pip python=3.5```

```activate tensorflow1```

2)Change the command below in 2d

```conda install -c anaconda protobuf```

to this

```pip install protobuf --upgrade```

3)Download protoc.exe from [here](https://github.com/google/protobuf/releases/download/v3.6.0/protoc-3.6.0-win32.zip) . Copy protoc.exe(in bin folder) to C:\tensorflow1\models\research.

Then run 2f.

4)Before step6, open C:\tensorflow1\models\research\object_detection\utils\learning_schedules.py with a text editor.

Change the line 168 from

```range(num_boundaries)```

```list(range(num_boundaries))```

# Data

Data can be downloaded from [here](https://www.kaggle.com/mbkinaci/fruit-images-for-object-detection). 240 training images 60 test images. No problematic image.

3 different types of fruits: Apple, Banana, Orange.

.xml files in data have coordinates of objects.

# Training

I trained it on a GTX 1050 for 5 hours. Approximately 53000 iterations.

# Implemented Model

Faster R CNN inception v2 model.

# Youtube Video

[![TensorFlow Object Detection API](https://github.com/MuhammedBuyukkinaci/Fruit-Detector/blob/master/images/my_ss.png)](https://www.youtube.com/watch?v=BCO1XdwUZYw&feature=youtu.be)

# Results on images

Input Image | Output Image
:-------------------------:|:-------------------------
|