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@@ -4,14 +4,15 @@ import math
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from scipy.ndimage.filters import gaussian_filter
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import torch
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-from service.aiutil import util
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-from service.aiutil.model import bodypose_model,bodypose_25_model
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+from service.ai.util import util
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+from service.ai.util.model import bodypose_model, bodypose_25_model
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import logging
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model_coco = 'model/body_coco.pth'
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model_body25 = 'model/body_25.pth'
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np.seterr(divide='ignore', invalid='ignore')
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+
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class torch_openpose(object):
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def __init__(self, model_type):
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if model_type == 'body_25':
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@@ -29,21 +30,20 @@ class torch_openpose(object):
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self.model = self.model.cuda()
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self.model.eval()
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- if self.njoint == 19: #coco
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+ if self.njoint == 19: # coco
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self.limbSeq = [[1, 2], [1, 5], [2, 3], [3, 4], [5, 6], [6, 7], [1, 8], [8, 9], \
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- [9, 10], [1, 11], [11, 12], [12, 13], [1, 0], [0, 14], [14, 16], \
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- [0, 15], [15, 17]]
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- self.mapIdx = [[12, 13],[20, 21],[14, 15],[16, 17],[22, 23],[24, 25],[0, 1],[2, 3],\
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- [4, 5],[6, 7],[8, 9],[10, 11],[28, 29],[30, 31],[34, 35],[32, 33],\
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- [36, 37]]
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- elif self.njoint == 26: #body_25
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- self.limbSeq = [[1,0],[1,2],[2,3],[3,4],[1,5],[5,6],[6,7],[1,8],[8,9],[9,10],\
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- [10,11],[8,12],[12,13],[13,14],[0,15],[0,16],[15,17],[16,18],\
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- [11,24],[11,22],[14,21],[14,19],[22,23],[19,20]]
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- self.mapIdx = [[30, 31],[14, 15],[16, 17],[18, 19],[22, 23],[24, 25],[26, 27],[0, 1],[6, 7],\
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- [2, 3],[4, 5], [8, 9],[10, 11],[12, 13],[32, 33],[34, 35],[36,37],[38,39],\
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- [50,51],[46,47],[44,45],[40,41],[48,49],[42,43]]
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-
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+ [9, 10], [1, 11], [11, 12], [12, 13], [1, 0], [0, 14], [14, 16], \
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+ [0, 15], [15, 17]]
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+ self.mapIdx = [[12, 13], [20, 21], [14, 15], [16, 17], [22, 23], [24, 25], [0, 1], [2, 3], \
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+ [4, 5], [6, 7], [8, 9], [10, 11], [28, 29], [30, 31], [34, 35], [32, 33], \
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+ [36, 37]]
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+ elif self.njoint == 26: # body_25
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+ self.limbSeq = [[1, 0], [1, 2], [2, 3], [3, 4], [1, 5], [5, 6], [6, 7], [1, 8], [8, 9], [9, 10], \
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+ [10, 11], [8, 12], [12, 13], [13, 14], [0, 15], [0, 16], [15, 17], [16, 18], \
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+ [11, 24], [11, 22], [14, 21], [14, 19], [22, 23], [19, 20]]
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+ self.mapIdx = [[30, 31], [14, 15], [16, 17], [18, 19], [22, 23], [24, 25], [26, 27], [0, 1], [6, 7], \
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+ [2, 3], [4, 5], [8, 9], [10, 11], [12, 13], [32, 33], [34, 35], [36, 37], [38, 39], \
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+ [50, 51], [46, 47], [44, 45], [40, 41], [48, 49], [42, 43]]
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def __call__(self, oriImg):
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# scale_search = [0.5, 1.0, 1.5, 2.0]
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@@ -107,7 +107,8 @@ class torch_openpose(object):
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map_down[:, :-1] = one_heatmap[:, 1:]
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peaks_binary = np.logical_and.reduce(
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- (one_heatmap >= map_left, one_heatmap >= map_right, one_heatmap >= map_up, one_heatmap >= map_down, one_heatmap > thre1))
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+ (one_heatmap >= map_left, one_heatmap >= map_right, one_heatmap >= map_up, one_heatmap >= map_down,
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+ one_heatmap > thre1))
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peaks = list(zip(np.nonzero(peaks_binary)[1], np.nonzero(peaks_binary)[0])) # note reverse
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peaks_with_score = [x + (map_ori[x[1], x[0]],) for x in peaks]
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peak_id = range(peak_counter, peak_counter + len(peaks))
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@@ -232,10 +233,8 @@ class torch_openpose(object):
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if po >= 0:
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joint = list(candidate[int(po)][:3])
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else:
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- joint = [0.,0.,0.]
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+ joint = [0., 0., 0.]
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pose.append(joint)
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poses.append(pose)
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return poses
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-
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-
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lyc8503