Re: [問題] 語法觀念一問

看板Python作者chengreg (想重回校園的工程師)時間2年前 (2021/06/22 12:10)推噓5(5推 0噓 17→)

留言22則, 5人參與討論串3/3 (看更多)

各位前輩,由於問題描述的太過簡略,容小弟詳細說明其程式碼來自 YOLO 的 predict result decoder,source code 如下 : netout #為Numpy NDarray anchors #為 Numpy DNarray obj_thresh #為 Float32 其數值為 0.6 net_h ,netw #為 int 其數值為 416 def decode_netout(netout, anchors, obj_thresh, net_h, net_w): grid_h, grid_w = netout.shape[:2] nb_box = 3 netout = netout.reshape((grid_h, grid_w, nb_box, -1)) nb_class = netout.shape[-1] - 5 boxes = [] netout[..., :2] = _sigmoid(netout[..., :2]) netout[..., 4:] = _sigmoid(netout[..., 4:]) netout[..., 5:] = netout[..., 4][..., np.newaxis] * netout[..., 5:] netout[..., 5:] *= netout[..., 5:] > obj_thresh for i in range(grid_h*grid_w): row = i / grid_w col = i % grid_w for b in range(nb_box): # 4th element is objectness score objectness = netout[int(row)][int(col)][b][4] if(objectness.all() <= obj_thresh): continue # first 4 elements are x, y, w, and h x, y, w, h = netout[int(row)][int(col)][b][:4] x = (col + x) / grid_w # center position, unit: image width y = (row + y) / grid_h # center position, unit: image height w = anchors[2 * b + 0] * np.exp(w) / net_w # unit: image width h = anchors[2 * b + 1] * np.exp(h) / net_h # unit: image height # last elements are class probabilities classes = netout[int(row)][col][b][5:] box = BoundBox(x-w/2, y-h/2, x+w/2, y+h/2, objectness, classes) boxes.append(box) return boxes 而小弟追蹤該 function 時發現該 objectness 為 float32 (請看截圖) 而無法理解該ojbectness為何會有 .all() 這個方法, 並且用來判斷 bool ? 一直無法理解這個問題故上來請教前輩們這個疑惑謝謝大家幫忙圖片如下 : https://photos.app.goo.gl/rbsPt91WBi1FcuvN6 -- ※ 發信站: 批踢踢實業坊(ptt.cc), 來自: 117.56.58.151 (臺灣) ※ 文章網址: https://www.ptt.cc/bbs/Python/M.1624335041.A.C7D.html

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penut85420

06/22 12:25, 2年前 , 1^F

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06/22 12:26, 2年前 , 2^F

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penut85420

06/22 12:26, 2年前 , 3^F

06/22 12:26, 3^F