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| import gradio as gr | |
| from predict import predict_masks | |
| import glob | |
| ##Create list of examples to be loaded | |
| example_list = glob.glob("examples/*") | |
| example_list = list(map(lambda el:[el], example_list)) | |
| demo = gr.Blocks() | |
| with demo: | |
| gr.Markdown("# **<p align='center'>Mask2Former: Masked Attention Mask Transformer for Universal Segmentation</p>**") | |
| gr.Markdown("This space demonstrates the use of Mask2Former. It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearch/Mask2Former/). \ | |
| Before Mask2Former, you'd have to resort to using a specialized architecture designed for solving a particular kind of image segmentation task (i.e. semantic, instance or panoptic segmentation). On the other hand, in the form of Mask2Former, for the first time, we have a single architecture that is capable of solving any segmentation task and performs on par or better than specialized architectures.") | |
| with gr.Box(): | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown("**Inputs**") | |
| segmentation_task = gr.Dropdown(["semantic", "instance", "panoptic"], value="panoptic", label="Segmentation Task", show_label=True) | |
| input_image = gr.Image(type='filepath',label="Input Image", show_label=True) | |
| with gr.Column(): | |
| gr.Markdown("**Outputs**") | |
| output_heading = gr.Textbox(label="Output Type", show_label=True) | |
| output_mask = gr.Image(label="Predicted Masks", show_label=True) | |
| gr.Markdown("**Predict**") | |
| with gr.Box(): | |
| with gr.Row(): | |
| submit_button = gr.Button("Submit") | |
| gr.Markdown("**Examples:**") | |
| with gr.Column(): | |
| gr.Examples(example_list, [input_image, segmentation_task], [output_mask,output_heading], predict_masks) | |
| submit_button.click(predict_masks, inputs=[input_image, segmentation_task], outputs=[output_mask,output_heading]) | |
| gr.Markdown('\n Demo created by: <a href=\"https://www.linkedin.com/in/shivalika-singh/\">Shivalika Singh</a>') | |
| demo.launch(debug=True) |