39 lines
1.1 KiB
Python
39 lines
1.1 KiB
Python
from typing import List
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from vision.model import Image
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class PrecisionRecall:
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def __init__(self, precision, recall, ap):
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self.precision = precision
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self.recall = recall
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self.ap = ap
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def get_precision(images: List[Image], test):
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return len([i for i in images if i.category == test]) / len(images)
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def get_recall(images: List[Image], test, category_count):
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return len([i for i in images if i.category == test]) / category_count
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def get_pr(images: List[Image], query: Image):
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images = sorted(images, key=lambda x: x.distance)
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query_category_count = len([i for i in images if i.category == query.category])
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p = []
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r = []
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for i in range(len(images)):
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p.append(get_precision(images[:i+1], query.category))
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r.append(get_recall(images[:i+1], query.category, query_category_count))
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precision_list = []
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for index, image in enumerate(images):
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if image.category == query.category:
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precision_list.append(p[index])
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ap = sum(precision_list) / query_category_count
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return PrecisionRecall(precision=p, recall=r, ap=ap)
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