File size: 2,795 Bytes
e0e832b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
import json
#import urllib.request, urllib.error, urllib.parse
import numpy as np
API = 'http://ec2-52-11-11-89.us-west-2.compute.amazonaws.com/challenge17/api.py'
def get_blocked_videos(api=API):
# api_url = '{}?action=get_blocked'.format(api)
# req = urllib.request.Request(api_url)
# response = urllib.request.urlopen(req)
# return json.loads(response.read())
return list()
def interpolated_prec_rec(prec, rec):
"""Interpolated AP - VOCdevkit from VOC 2011.
"""
mprec = np.hstack([[0], prec, [0]])
mrec = np.hstack([[0], rec, [1]])
for i in range(len(mprec) - 1)[::-1]:
mprec[i] = max(mprec[i], mprec[i + 1])
idx = np.where(mrec[1::] != mrec[0:-1])[0] + 1
ap = np.sum((mrec[idx] - mrec[idx - 1]) * mprec[idx])
return ap
def segment_iou(target_segment, candidate_segments):
"""Compute the temporal intersection over union between a
target segment and all the test segments.
Parameters
----------
target_segment : 1d array
Temporal target segment containing [starting, ending] times.
candidate_segments : 2d array
Temporal candidate segments containing N x [starting, ending] times.
Outputs
-------
tiou : 1d array
Temporal intersection over union score of the N's candidate segments.
"""
tt1 = np.maximum(target_segment[0], candidate_segments[:, 0])
tt2 = np.minimum(target_segment[1], candidate_segments[:, 1])
# Intersection including Non-negative overlap score.
segments_intersection = (tt2 - tt1).clip(0)
# Segment union.
segments_union = (candidate_segments[:, 1] - candidate_segments[:, 0]) \
+ (target_segment[1] - target_segment[0]) - segments_intersection
# Compute overlap as the ratio of the intersection
# over union of two segments.
tIoU = segments_intersection.astype(float) / segments_union
return tIoU
def wrapper_segment_iou(target_segments, candidate_segments):
"""Compute intersection over union btw segments
Parameters
----------
target_segments : ndarray
2-dim array in format [m x 2:=[init, end]]
candidate_segments : ndarray
2-dim array in format [n x 2:=[init, end]]
Outputs
-------
tiou : ndarray
2-dim array [n x m] with IOU ratio.
Note: It assumes that candidate-segments are more scarce that target-segments
"""
if candidate_segments.ndim != 2 or target_segments.ndim != 2:
raise ValueError('Dimension of arguments is incorrect')
n, m = candidate_segments.shape[0], target_segments.shape[0]
tiou = np.empty((n, m))
for i in range(m):
tiou[:, i] = segment_iou(target_segments[i,:], candidate_segments)
return tiou
|