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Upload mobilenet_v2 and yolov3_tiny
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README.md

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## Compare different model by using same dataset
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1. [YoloV2](https://github.com/eric612/yolov2-windows)
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1. [YoloV3](https://pjreddie.com/darknet/yolo/)
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2. [FasterRCNN](https://github.com/intel/caffe)
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3. [MobileNet SSD](https://github.com/eric612/MobileNet-SSD-windows)
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3. [MobileNet(V2) SSD](https://github.com/eric612/MobileNet-SSD-windows)
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### YOLOv3 Tiny Result
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[![IMAGE ALT TEXT HERE](https://img.youtube.com/vi/rA5nHltRGRE/1000.jpg)](https://www.youtube.com/watch?v=rA5nHltRGRE)
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### Customize YOLOv2
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1. Better performance on small vehicle detection , but will add false object more
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2. light weight (30M , 27% size of full yolov2)
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3. 1.5x faster of full yolov2 (CPU forward)
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4. Only has conv,max pooling and region loss layer
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### YOLOv3 Tiny Model
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#### Result
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[weights](\YOLO\yolov3-tiny.cfg)
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[![1](https://img.youtube.com/vi/9pS3Ov_b-Qg/0.jpg)](https://www.youtube.com/watch?v=9pS3Ov_b-Qg)
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[model](\YOLO\yolov3-tiny_final.weights)
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[![1](https://img.youtube.com/vi/EU51rO3M6yo/0.jpg)](https://www.youtube.com/watch?v=EU51rO3M6yo)
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[![1](https://img.youtube.com/vi/cKW5MVIlGMg/0.jpg)](https://www.youtube.com/watch?v=cKW5MVIlGMg)
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#### Training
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weights download [here](https://drive.google.com/open?id=1Ul8yRlvzcr8nsn5yfm9G_pdxqHVYsryY)
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### MobileNetSSD Model
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train command
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```
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darknet detector train data/voc.data yolo-voc-custom.cfg car.conv.14
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```
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[weights](https://drive.google.com/open?id=1LbLSTPFSlHML5qAUYN-kt1bw2HxvvNWS)
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### Original YOLOv2
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[model](https://drive.google.com/open?id=1KOE5r-71FFWU0LZbpo9HMEUwM_RE1LHR)
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#### Model download
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### MobileNetSSD_V2 Model
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weights download [here](https://drive.google.com/open?id=1pfGqD00STsauvBAnj6UyzNlgSJugm89q)
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[weights] (https://drive.google.com/open?id=1v5X4tCaMFa59cfS4Ksr1J-Fl40vKlfpl)
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#### Result
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[model](https://github.com/eric612/MobileNet-SSD-windows/blob/master/models/MobileNetV2/deploy.prototxt)
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[![1](https://img.youtube.com/vi/kuKnOTDIbq4/0.jpg)](https://www.youtube.com/watch?v=kuKnOTDIbq4)
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### MobileNetSSD Result
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[![2](https://img.youtube.com/vi/OlNxMPkwxyQ/0.jpg)](https://www.youtube.com/watch?v=OlNxMPkwxyQ)
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[![IMAGE ALT TEXT HERE](https://img.youtube.com/vi/jn6SOzT_wPA/0.jpg)](https://www.youtube.com/watch?v=jn6SOzT_wPA)
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[![3](https://img.youtube.com/vi/FEb4SWWBjLA/0.jpg)](https://www.youtube.com/watch?v=FEb4SWWBjLA)
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### MobileNetSSD_V2 Result
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[![4](https://img.youtube.com/vi/WThUZUfJMMQ/0.jpg)](https://www.youtube.com/watch?v=WThUZUfJMMQ)
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[![IMAGE ALT TEXT HERE](https://img.youtube.com/vi/oc3tXxOoSH4/0.jpg)](https://www.youtube.com/watch?v=oc3tXxOoSH4)
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[![5](https://img.youtube.com/vi/3KSccLecHEM/0.jpg)](https://www.youtube.com/watch?v=3KSccLecHEM)
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### FasterRCNN Model
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[![IMAGE ALT TEXT HERE](https://img.youtube.com/vi/xjIB9t1tLOg/0.jpg)](https://www.youtube.com/watch?v=xjIB9t1tLOg)
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### MobileNetSSD Model
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[weights](https://drive.google.com/open?id=1LbLSTPFSlHML5qAUYN-kt1bw2HxvvNWS)
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[model](https://drive.google.com/open?id=1KOE5r-71FFWU0LZbpo9HMEUwM_RE1LHR)
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### MobileNetSSD Result
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[![IMAGE ALT TEXT HERE](https://img.youtube.com/vi/jn6SOzT_wPA/0.jpg)](https://www.youtube.com/watch?v=jn6SOzT_wPA)
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### Source Video
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