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| from gradio.outputs import Label | |
| from icevision import tfms | |
| from icevision.models.checkpoint import model_from_checkpoint | |
| import PIL | |
| import gradio as gr | |
| import os | |
| detection_threshold = 0.7 | |
| checkpoint_path = "2022-10-03_resnet_slates_147.pth" | |
| description = ( | |
| "A faster-rcnn model that detects film slates / clappers. " | |
| "Upload an image of a slate or click an example below!" | |
| ) | |
| # Load model | |
| checkpoint_and_model = model_from_checkpoint(checkpoint_path) | |
| model = checkpoint_and_model["model"] | |
| model_type = checkpoint_and_model["model_type"] | |
| class_map = checkpoint_and_model["class_map"] | |
| # Transforms | |
| img_size = checkpoint_and_model["img_size"] | |
| valid_tfms = tfms.A.Adapter( | |
| [*tfms.A.resize_and_pad(img_size), tfms.A.Normalize()] | |
| ) | |
| # Populate examples in Gradio interface | |
| examples = [ | |
| ["1.jpg"], | |
| ["2.jpg"], | |
| ["3.jpg"], | |
| ] | |
| def show_preds(input_image): | |
| img = PIL.Image.fromarray(input_image, "RGB") | |
| pred_dict = model_type.end2end_detect( | |
| img, | |
| valid_tfms, | |
| model, | |
| class_map=class_map, | |
| detection_threshold=detection_threshold, | |
| display_label=False, | |
| display_bbox=True, | |
| return_img=True, | |
| font_size=16, | |
| label_color="#02D800", | |
| ) | |
| return pred_dict["img"] | |
| gr_interface = gr.Interface( | |
| fn=show_preds, | |
| inputs=["image"], | |
| outputs=[gr.outputs.Image(type="pil", label="Inference")], | |
| title="Film Slate Detector", | |
| description=description, | |
| examples=examples, | |
| ) | |
| gr_interface.launch(inline=False, share=False, debug=True) | |