devhkyu/Smart_Coordinator

To predict fashion trend, to recommend your style

Image Data

iMaterialist Fashion 2019 at FGVC6 (Mask R-CNN: Object Detection)

• https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6/data
• train.csv
• train.zip
• test.zip
• label_descriptions.json (In git, we already have)

Image Crawling (CNN: Classification, Similarity)

• Camscon (https://camscon.kr/)
• FashionGio (http://www.fashiongio.com/)
• Sn@pp (http://zine.istyle24.com/)
• Musinsa (https://www.musinsa.com/)
• Instagram (http://instagram.com/)
• Google Image Search (http://google.com/)

Mask_RCNN

• https://github.com/matterport/Mask_RCNN

Weight file

• fashion20191028T0500/mask_rcnn_fashion_0006.h5 (256.83Mb)
• mask_rcnn_coco.h5 (245.6Mb)
• If you want to download these files, please contact e-mail (fab@kakao.com)

Module Version

• Tensorflow (1.14.0) - If version of tensorflow is the latest, some errors will occur.
• Keras (2.3.0) - If you want to run server(main.py), you should install keras (2.2.5)
• Numpy (<1.17) - If you don't want to see FutureWarnings, you should install numpy (<1.17). If not, Numpy version doesn't matter.

pip install tensorflow==1.14.0
pip install keras==2.2.5
pip install "numpy<1.17"

Errors

• AttributeError: 'Model' object has no attribute 'metrics_tensors'

• Mask_RCNN/mrcnn/model.py line 2191:

    # Add metrics for losses
    for name in loss_names:
        self.keras_model.metrics_tensors = []   # You should add this code
        if name in self.keras_model.metrics_names:
            continue
        layer = self.keras_model.get_layer(name)
        self.keras_model.metrics_names.append(name)
        loss = (
            tf.reduce_mean(layer.output, keepdims=True)
            * self.config.LOSS_WEIGHTS.get(name, 1.))
        self.keras_model.metrics_tensors.append(loss)
  

License

Copyright 2020 ChoiHyungKyu (Hyungkyu Choi)

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

   http://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.