44 lines
847 B
Python
Executable File
44 lines
847 B
Python
Executable File
import json
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import glob
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import numpy as np
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import matplotlib.pyplot as plt
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from tqdm import tqdm
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from multiprocessing import Pool
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from utils.labelme import get_mask_v2
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from utils.e2e_metrics import get_metrics
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def get_score():
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res = []
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for id in range(nums):
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res += [get_metrics(
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label[id],
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get_mask_v2(pred[id])
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)]
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return res
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def get_score_v():
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res = []
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for id in range(nums):
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res += [get_metrics(
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np.array(label[id] > 0),
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get_mask_v2(pred[id])
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)]
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return res
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with open('/home/gao/mouclear/cc/code_v2/msunet/logs/0/version_0/test.json') as f:
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data = json.load(f)
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label = np.array(data['label']) # [metric_idx]
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pred = np.array(data['pred']) # [metric_idx]
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nums = label.shape[0]; nums
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b = get_score_v()
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print(np.mean(b, axis=0)) |