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| import streamlit.components.v1 as components | |
| import numpy | |
| import sahi.predict | |
| import sahi.utils | |
| from PIL import Image | |
| import base64 | |
| import io | |
| def sahi_mmdet_inference( | |
| image, | |
| detection_model, | |
| slice_height=512, | |
| slice_width=512, | |
| overlap_height_ratio=0.2, | |
| overlap_width_ratio=0.2, | |
| image_size=640, | |
| postprocess_type="UNIONMERGE", | |
| postprocess_match_metric="IOS", | |
| postprocess_match_threshold=0.5, | |
| postprocess_class_agnostic=False, | |
| ): | |
| # standard inference | |
| prediction_result_1 = sahi.predict.get_prediction( | |
| image=image, detection_model=detection_model, image_size=image_size | |
| ) | |
| visual_result_1 = sahi.utils.cv.visualize_object_predictions( | |
| image=numpy.array(image), | |
| object_prediction_list=prediction_result_1.object_prediction_list, | |
| ) | |
| output_1 = Image.fromarray(visual_result_1["image"]) | |
| # sliced inference | |
| prediction_result_2 = sahi.predict.get_sliced_prediction( | |
| image=image, | |
| detection_model=detection_model, | |
| image_size=image_size, | |
| slice_height=slice_height, | |
| slice_width=slice_width, | |
| overlap_height_ratio=overlap_height_ratio, | |
| overlap_width_ratio=overlap_width_ratio, | |
| postprocess_type=postprocess_type, | |
| postprocess_match_metric=postprocess_match_metric, | |
| postprocess_match_threshold=postprocess_match_threshold, | |
| postprocess_class_agnostic=postprocess_class_agnostic, | |
| ) | |
| visual_result_2 = sahi.utils.cv.visualize_object_predictions( | |
| image=numpy.array(image), | |
| object_prediction_list=prediction_result_2.object_prediction_list, | |
| ) | |
| output_2 = Image.fromarray(visual_result_2["image"]) | |
| return output_1, output_2 | |
| def pillow_to_base64(image: Image.Image): | |
| in_mem_file = io.BytesIO() | |
| image.save(in_mem_file, format="PNG") | |
| img_bytes = in_mem_file.getvalue() # bytes | |
| image_str = base64.b64encode(img_bytes).decode("utf-8") | |
| base64_src = f"data:image/png;base64,{image_str}" | |
| return base64_src | |
| def imagecompare( | |
| img1: str, | |
| img2: str, | |
| label1: str = "1", | |
| label2: str = "2", | |
| width: int = 700, | |
| show_labels: bool = True, | |
| starting_position: int = 50, | |
| make_responsive: bool = True, | |
| ): | |
| """Create a new juxtapose component. | |
| Parameters | |
| ---------- | |
| img1: str, PosixPath, PIL.Image or URL | |
| Input image to compare | |
| img2: str, PosixPath, PIL.Image or URL | |
| Input image to compare | |
| label1: str or None | |
| Label for image 1 | |
| label2: str or None | |
| Label for image 2 | |
| width: int or None | |
| Width of the component in px | |
| show_labels: bool or None | |
| Show given labels on images | |
| starting_position: int or None | |
| Starting position of the slider as percent (0-100) | |
| make_responsive: bool or None | |
| Enable responsive mode | |
| Returns | |
| ------- | |
| static_component: Boolean | |
| Returns a static component with a timeline | |
| """ | |
| # prepare images | |
| img_width, img_height = img1.size | |
| h_to_w = img_height / img_width | |
| height = (width * h_to_w) * 0.95 | |
| img1 = pillow_to_base64(sahi.utils.cv.read_image_as_pil(img1)) | |
| img2 = pillow_to_base64(sahi.utils.cv.read_image_as_pil(img2)) | |
| # load css + js | |
| cdn_path = "https://cdn.knightlab.com/libs/juxtapose/latest" | |
| css_block = f'<link rel="stylesheet" href="{cdn_path}/css/juxtapose.css">' | |
| js_block = f'<script src="{cdn_path}/js/juxtapose.min.js"></script>' | |
| # write html block | |
| htmlcode = f""" | |
| {css_block} | |
| {js_block} | |
| <div id="foo"style="height: {height}; width: {width or '%100'};"></div> | |
| <script> | |
| slider = new juxtapose.JXSlider('#foo', | |
| [ | |
| {{ | |
| src: '{img1}', | |
| label: '{label1}', | |
| }}, | |
| {{ | |
| src: '{img2}', | |
| label: '{label2}', | |
| }} | |
| ], | |
| {{ | |
| animate: true, | |
| showLabels: {'true' if show_labels else 'false'}, | |
| showCredits: true, | |
| startingPosition: "{starting_position}%", | |
| makeResponsive: {'true' if make_responsive else 'false'}, | |
| }}); | |
| </script> | |
| """ | |
| static_component = components.html(htmlcode, height=height, width=width) | |
| return static_component | |