Update Human-Embryo-Timelapse.py
Browse files- Human-Embryo-Timelapse.py +11 -11
Human-Embryo-Timelapse.py
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@@ -6,16 +6,16 @@ from PIL import ImageFile
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ImageFile.LOAD_TRUNCATED_IMAGES = True
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_URLS = {
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"F-45": "https://zenodo.org/records/7912264/files/embryo_dataset_F-45.tar.gz",
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"F-30": "https://zenodo.org/records/7912264/files/embryo_dataset_F-30.tar.gz",
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"F-15": "https://zenodo.org/records/7912264/files/embryo_dataset_F-15.tar.gz",
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"F0": "https://zenodo.org/records/7912264/files/embryo_dataset.tar.gz",
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"F+15": "https://zenodo.org/records/7912264/files/embryo_dataset_F15.tar.gz",
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"F+30": "https://zenodo.org/records/7912264/files/embryo_dataset_F30.tar.gz",
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"F+45": "https://zenodo.org/records/7912264/files/embryo_dataset_F45.tar.gz",
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"grades": "https://zenodo.org/records/7912264/files/embryo_dataset_grades.csv",
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"annotations": "https://zenodo.org/records/7912264/files/embryo_dataset_annotations.tar.gz",
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"time_elapsed": "https://zenodo.org/records/7912264/files/embryo_dataset_time_elapsed.tar.gz",
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}
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_EVENT_NAMES = [
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@@ -98,7 +98,7 @@ class HumanEmbryoTimelapse(datasets.GeneratorBasedBuilder):
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"""Generate images and labels for splits."""
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# get grades for each embryo (name, TE, ICM)
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pd_grades = pd.read_csv(directories["grades"],
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grades = {
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row["video_name"]: {
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"TE": row["TE"],
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ImageFile.LOAD_TRUNCATED_IMAGES = True
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_URLS = {
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"F-45": "https://zenodo.org/records/7912264/files/embryo_dataset_F-45.tar.gz?download=1",
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"F-30": "https://zenodo.org/records/7912264/files/embryo_dataset_F-30.tar.gz?download=1",
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"F-15": "https://zenodo.org/records/7912264/files/embryo_dataset_F-15.tar.gz?download=1",
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"F0": "https://zenodo.org/records/7912264/files/embryo_dataset.tar.gz?download=1",
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"F+15": "https://zenodo.org/records/7912264/files/embryo_dataset_F15.tar.gz?download=1",
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"F+30": "https://zenodo.org/records/7912264/files/embryo_dataset_F30.tar.gz?download=1",
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"F+45": "https://zenodo.org/records/7912264/files/embryo_dataset_F45.tar.gz?download=1",
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"grades": "https://zenodo.org/records/7912264/files/embryo_dataset_grades.csv?download=1",
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"annotations": "https://zenodo.org/records/7912264/files/embryo_dataset_annotations.tar.gz?download=1",
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"time_elapsed": "https://zenodo.org/records/7912264/files/embryo_dataset_time_elapsed.tar.gz?download=1",
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}
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_EVENT_NAMES = [
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"""Generate images and labels for splits."""
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# get grades for each embryo (name, TE, ICM)
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pd_grades = pd.read_csv(directories["grades"], keep_default_na=False)
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grades = {
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row["video_name"]: {
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"TE": row["TE"],
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