huhulaoxian / EndtoEndCroppingSystem

End-to-End Cropping System

This is an offical implemenation for An End-to-End Neural Network for Image Cropping by Learning Composition from Aesthetic Photos.

Given a source image, our algorithm could take actions step by step to find almost the best cropping window on source image.

Get Start

Install the python libraries. (See Requirements).

Download the code from GitHub:

git clone https://github.com/CVBase-Bupt/EndtoEndCroppingSystem.git

cd EndtoEndCroppingSystem

Run the python script:

python demo.py [your image path]

Before you run, please download our pre-trained models.We have released 6 models based on different scale (224,384,512) and ratio (square or not). If you want to use any of them, just:

link：https://pan.baidu.com/s/11m4mNhUdFUlTThRXDL7XLA password：vzwb

Put the weight file under the dirctory weights

Fix the config file models/config.py, change the self.ratio and self.scale in the __init__function.

Requirement

Python

keras(we use version 2.2.4)

tensorflow 1.13.1

opencv-python 2.4.9

Performance

On FLMS:

model	IOU	BDE
model__224	0.846	0.026
model__384	0.844	0.027
model__512	0.845	0.028
model_square_224	0.840	0.028
model_square_384	0.843	0.028
model_square_512	0.842	0.028

On CUHK-ICD:

model	IOU	BDE	IOU	BDE	IOU	BDE
model__224	0.822	0.032	0.815	0.034	0.803	0.036
model__384	0.823	0.032	0.818	0.034	0.804	0.036
model__512	0.825	0.032	0.820	0.034	0.806	0.036
model_square_224	0.825	0.032	0.818	0.034	0.805	0.036
model_square_384	0.827	0.032	0.817	0.034	0.804	0.036
model_square_512	0.828	0.032	0.822	0.034	0.806	0.036

On FCD:

model	IOU	BDE
model__224	0.673	0.058
model__384	0.670	0.059
model__512	0.664	0.060
model_square_224	0.672	0.059
model_square_384	0.670	0.059
model_square_512	0.665	0.061