Spaces:
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Daniel Cerda Escobar
commited on
Commit
·
7bb89fc
1
Parent(s):
55018fa
Bugs Fixed
Browse files- requirements.txt +2 -4
- utils.py +8 -40
requirements.txt
CHANGED
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@@ -1,7 +1,5 @@
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sahi==0.11.14
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streamlit-image-comparison==0.0.4
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streamlit
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ultralyticsplus
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pdf2image
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PyPDF4
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sahi==0.11.14
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streamlit-image-comparison==0.0.4
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streamlit
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ultralyticsplus
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utils.py
CHANGED
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@@ -1,8 +1,6 @@
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import numpy
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import sahi.predict
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import sahi.utils
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import PyPDF4
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from pdf2image import convert_from_path
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from PIL import Image
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TEMP_DIR = "temp"
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@@ -15,55 +13,25 @@ def sahi_yolov8m_inference(
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slice_width=512,
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overlap_height_ratio=0.1,
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overlap_width_ratio=0.1,
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image_size=
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postprocess_match_threshold=0.
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):
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# standard inference
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detection_model.image_size = image_size
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prediction_result_1 = sahi.predict.get_prediction(
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image=image, detection_model=detection_model
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)
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visual_result_1 = sahi.utils.cv.visualize_object_predictions(
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image=numpy.array(image),
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object_prediction_list=prediction_result_1.object_prediction_list,
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)
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output_1 = Image.fromarray(visual_result_1["image"])
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# sliced inference
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image=image,
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detection_model=detection_model,
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slice_height=slice_height,
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slice_width=slice_width,
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overlap_height_ratio=overlap_height_ratio,
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overlap_width_ratio=overlap_width_ratio,
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postprocess_match_threshold=postprocess_match_threshold,
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)
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image=numpy.array(image),
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object_prediction_list=
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)
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return output_1, output_2
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# path,
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# #filename=name,
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# dpi=300,
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# image_width=4961,
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# image_heigth=3508,
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# grayscale=True,
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# ):
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# with open(path, 'rb') as pdf_file:
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# pdf_reader = PyPDF4.PdfFileReader(pdf_file, strict=False)
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# first_page = pdf_reader.getPage(0)
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# page_size = (first_page.mediaBox.getWidth(), first_page.mediaBox.getHeight())
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# if page_size[0] > page_size[1]:
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# image = convert_from_path(path, dpi=dpi, size=(image_width,image_heigth), grayscale=grayscale)
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# else:
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# image = convert_from_path(path, dpi=dpi, size=(image_heigth,image_width), grayscale=grayscale)
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# return image
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# image[0].save(f'{path}/{filename}.png', 'PNG')
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import numpy
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import sahi.predict
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import sahi.utils
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from PIL import Image
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TEMP_DIR = "temp"
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slice_width=512,
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overlap_height_ratio=0.1,
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overlap_width_ratio=0.1,
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image_size=1024,
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postprocess_match_threshold=0.75,
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):
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# sliced inference
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prediction_result = sahi.predict.get_sliced_prediction(
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image=image,
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detection_model=detection_model,
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image_size = image_size,
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slice_height=slice_height,
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slice_width=slice_width,
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overlap_height_ratio=overlap_height_ratio,
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overlap_width_ratio=overlap_width_ratio,
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postprocess_match_threshold=postprocess_match_threshold,
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)
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visual_result = sahi.utils.cv.visualize_object_predictions(
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image=numpy.array(image),
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object_prediction_list=prediction_result.object_prediction_list,
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)
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output = Image.fromarray(visual_result["image"])
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return output
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