| ## Detecting the Orientation of CelebA pictures using Deep Learning | |
| This model has been trained on a modified version of the CelebA dataset, which was made from flipping 20,000 and keeping 20,000 images intact. | |
| The model relies on Resnet-18 as a backbone and then is connected to one output node to classify whether images are flipped upside down (1) or not (0). | |
| --- | |
| language: | |
| - en | |
| license: apache-2.0 | |
| tags: | |
| - {image-classification} | |
| - {pytorch} | |
| datasets: | |
| - CelebA-faces | |
| model-index: | |
| - name: celebA_orientation_detection_model | |
| results: | |
| - task: | |
| type: image_classification # Required. Example: automatic-speech-recognition | |
| name: Image Classification # Optional. Example: Speech Recognition | |
| dataset: | |
| type: CelebA-faces | |
| name: CelebA-faces | |
| metrics: | |
| - type: f1score # Required. Example: wer | |
| value: 0.97 # Required. Example: 20.90 | |
| name: Val F1 Score # Optional. Example: Test WER | |
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