88 lines
3.2 KiB
Python
88 lines
3.2 KiB
Python
import paddle
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import numpy as np
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import copy
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def org_tcl_rois(batch_size, pos_lists, pos_masks, label_lists, tcl_bs):
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"""
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"""
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pos_lists_, pos_masks_, label_lists_ = [], [], []
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img_bs = batch_size
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ngpu = int(batch_size / img_bs)
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img_ids = np.array(pos_lists, dtype=np.int32)[:, 0, 0].copy()
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pos_lists_split, pos_masks_split, label_lists_split = [], [], []
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for i in range(ngpu):
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pos_lists_split.append([])
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pos_masks_split.append([])
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label_lists_split.append([])
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for i in range(img_ids.shape[0]):
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img_id = img_ids[i]
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gpu_id = int(img_id / img_bs)
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img_id = img_id % img_bs
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pos_list = pos_lists[i].copy()
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pos_list[:, 0] = img_id
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pos_lists_split[gpu_id].append(pos_list)
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pos_masks_split[gpu_id].append(pos_masks[i].copy())
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label_lists_split[gpu_id].append(copy.deepcopy(label_lists[i]))
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# repeat or delete
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for i in range(ngpu):
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vp_len = len(pos_lists_split[i])
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if vp_len <= tcl_bs:
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for j in range(0, tcl_bs - vp_len):
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pos_list = pos_lists_split[i][j].copy()
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pos_lists_split[i].append(pos_list)
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pos_mask = pos_masks_split[i][j].copy()
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pos_masks_split[i].append(pos_mask)
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label_list = copy.deepcopy(label_lists_split[i][j])
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label_lists_split[i].append(label_list)
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else:
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for j in range(0, vp_len - tcl_bs):
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c_len = len(pos_lists_split[i])
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pop_id = np.random.permutation(c_len)[0]
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pos_lists_split[i].pop(pop_id)
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pos_masks_split[i].pop(pop_id)
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label_lists_split[i].pop(pop_id)
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# merge
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for i in range(ngpu):
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pos_lists_.extend(pos_lists_split[i])
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pos_masks_.extend(pos_masks_split[i])
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label_lists_.extend(label_lists_split[i])
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return pos_lists_, pos_masks_, label_lists_
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def pre_process(label_list, pos_list, pos_mask, max_text_length, max_text_nums,
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pad_num, tcl_bs):
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label_list = label_list.numpy()
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batch, _, _, _ = label_list.shape
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pos_list = pos_list.numpy()
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pos_mask = pos_mask.numpy()
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pos_list_t = []
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pos_mask_t = []
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label_list_t = []
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for i in range(batch):
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for j in range(max_text_nums):
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if pos_mask[i, j].any():
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pos_list_t.append(pos_list[i][j])
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pos_mask_t.append(pos_mask[i][j])
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label_list_t.append(label_list[i][j])
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pos_list, pos_mask, label_list = org_tcl_rois(batch, pos_list_t, pos_mask_t,
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label_list_t, tcl_bs)
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label = []
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tt = [l.tolist() for l in label_list]
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for i in range(tcl_bs):
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k = 0
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for j in range(max_text_length):
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if tt[i][j][0] != pad_num:
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k += 1
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else:
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break
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label.append(k)
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label = paddle.to_tensor(label)
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label = paddle.cast(label, dtype='int64')
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pos_list = paddle.to_tensor(pos_list)
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pos_mask = paddle.to_tensor(pos_mask)
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label_list = paddle.squeeze(paddle.to_tensor(label_list), axis=2)
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label_list = paddle.cast(label_list, dtype='int32')
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return pos_list, pos_mask, label_list, label
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