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| import subprocess | |
| import sys | |
| print("Reinstalling mmcv") | |
| subprocess.check_call([sys.executable, "-m", "pip", "uninstall", "-y", "mmcv-full==1.3.17"]) | |
| subprocess.check_call([sys.executable, "-m", "pip", "install", "mmcv-full==1.3.17", "-f", "https://download.openmmlab.com/mmcv/dist/cpu/torch1.10.0/index.html"]) | |
| print("mmcv install complete") | |
| from icevision.all import * | |
| from icevision.models.checkpoint import * | |
| import PIL | |
| import gradio as gr | |
| import os | |
| # Load model | |
| checkpoint_path = 'models/model_checkpoint.pth' | |
| 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()]) | |
| for root, dirs, files in os.walk(r'sample_images/'): | |
| for filename in files: | |
| print(filename) | |
| examples = ["sample_images/"+file for file in files] | |
| article="<p style='text-align: center'><a href='https://dicksonneoh.com/' target='_blank'>Blog post</a></p>" | |
| enable_queue=True | |
| #examples = [['sample_images/3.jpg']] | |
| examples = [["sample_images/"+file] for file in files] | |
| def show_preds(input_image, display_label, display_bbox, detection_threshold): | |
| if detection_threshold==0: detection_threshold=0.5 | |
| 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=display_label, display_bbox=display_bbox, return_img=True, | |
| font_size=16, label_color="#FF59D6") | |
| return pred_dict['img'] | |
| # display_chkbox = gr.inputs.CheckboxGroup(["Label", "BBox"], label="Display", default=True) | |
| display_chkbox_label = gr.inputs.Checkbox(label="Label", default=True) | |
| display_chkbox_box = gr.inputs.Checkbox(label="Box", default=True) | |
| detection_threshold_slider = gr.inputs.Slider(minimum=0, maximum=1, step=0.1, default=0.5, label="Detection Threshold") | |
| outputs = gr.outputs.Image(type="pil") | |
| # Option 1: Get an image from local drive | |
| gr_interface = gr.Interface(fn=show_preds, inputs=["image", display_chkbox_label, display_chkbox_box, detection_threshold_slider], outputs=outputs, title='Microalgae Detection', article=article, examples=examples) | |
| # # Option 2: Grab an image from a webcam | |
| # gr_interface = gr.Interface(fn=show_preds, inputs=["webcam", display_chkbox_label, display_chkbox_box, detection_threshold_slider], outputs=outputs, title='IceApp - COCO', live=False) | |
| # # Option 3: Continuous image stream from the webcam | |
| # gr_interface = gr.Interface(fn=show_preds, inputs=["webcam", display_chkbox_label, display_chkbox_box, detection_threshold_slider], outputs=outputs, title='IceApp - COCO', live=True) | |
| gr_interface.launch(inline=False, share=True, debug=True) | |