Merge branch 'dygraph' of https://github.com/PaddlePaddle/PaddleOCR into dygraph

configs/table/table_mv3.yml

@@ -43,7 +43,6 @@ Architecture:
   Head:
     name: TableAttentionHead
     hidden_size: 256
-    loc_type: 2
     max_text_length: *max_text_length
     loc_reg_num: &loc_reg_num 4
 

ppocr/modeling/heads/table_att_head.py

@@ -16,6 +16,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import math
 import paddle
 import paddle.nn as nn
 from paddle import ParamAttr
@@ -42,7 +43,6 @@ class TableAttentionHead(nn.Layer):
     def __init__(self,
                  in_channels,
                  hidden_size,
-                 loc_type,
                  in_max_len=488,
                  max_text_length=800,
                  out_channels=30,
@@ -57,20 +57,16 @@ class TableAttentionHead(nn.Layer):
         self.structure_attention_cell = AttentionGRUCell(
             self.input_size, hidden_size, self.out_channels, use_gru=False)
         self.structure_generator = nn.Linear(hidden_size, self.out_channels)
-        self.loc_type = loc_type
         self.in_max_len = in_max_len
 
-        if self.loc_type == 1:
-            self.loc_generator = nn.Linear(hidden_size, 4)
+        if self.in_max_len == 640:
+            self.loc_fea_trans = nn.Linear(400, self.max_text_length + 1)
+        elif self.in_max_len == 800:
+            self.loc_fea_trans = nn.Linear(625, self.max_text_length + 1)
         else:
-            if self.in_max_len == 640:
-                self.loc_fea_trans = nn.Linear(400, self.max_text_length + 1)
-            elif self.in_max_len == 800:
-                self.loc_fea_trans = nn.Linear(625, self.max_text_length + 1)
-            else:
-                self.loc_fea_trans = nn.Linear(256, self.max_text_length + 1)
-            self.loc_generator = nn.Linear(self.input_size + hidden_size,
-                                           loc_reg_num)
+            self.loc_fea_trans = nn.Linear(256, self.max_text_length + 1)
+        self.loc_generator = nn.Linear(self.input_size + hidden_size,
+                                       loc_reg_num)
 
     def _char_to_onehot(self, input_char, onehot_dim):
         input_ont_hot = F.one_hot(input_char, onehot_dim)
@@ -80,16 +76,13 @@ class TableAttentionHead(nn.Layer):
         # if and else branch are both needed when you want to assign a variable
         # if you modify the var in just one branch, then the modification will not work.
         fea = inputs[-1]
-        if len(fea.shape) == 3:
-            pass
-        else:
-            last_shape = int(np.prod(fea.shape[2:]))  # gry added
-            fea = paddle.reshape(fea, [fea.shape[0], fea.shape[1], last_shape])
-            fea = fea.transpose([0, 2, 1])  # (NTC)(batch, width, channels)
+        last_shape = int(np.prod(fea.shape[2:]))  # gry added
+        fea = paddle.reshape(fea, [fea.shape[0], fea.shape[1], last_shape])
+        fea = fea.transpose([0, 2, 1])  # (NTC)(batch, width, channels)
         batch_size = fea.shape[0]
 
         hidden = paddle.zeros((batch_size, self.hidden_size))
-        output_hiddens = []
+        output_hiddens = paddle.zeros((batch_size, self.max_text_length + 1, self.hidden_size))
         if self.training and targets is not None:
             structure = targets[0]
             for i in range(self.max_text_length + 1):
@@ -97,7 +90,8 @@ class TableAttentionHead(nn.Layer):
                     structure[:, i], onehot_dim=self.out_channels)
                 (outputs, hidden), alpha = self.structure_attention_cell(
                     hidden, fea, elem_onehots)
-                output_hiddens.append(paddle.unsqueeze(outputs, axis=1))
+                output_hiddens[:, i, :] = outputs
+                # output_hiddens.append(paddle.unsqueeze(outputs, axis=1))
             output = paddle.concat(output_hiddens, axis=1)
             structure_probs = self.structure_generator(output)
             if self.loc_type == 1:
@@ -118,30 +112,25 @@ class TableAttentionHead(nn.Layer):
             outputs = None
             alpha = None
             max_text_length = paddle.to_tensor(self.max_text_length)
-            i = 0
-            while i < max_text_length + 1:
+            for i in range(max_text_length + 1):
                 elem_onehots = self._char_to_onehot(
                     temp_elem, onehot_dim=self.out_channels)
                 (outputs, hidden), alpha = self.structure_attention_cell(
                     hidden, fea, elem_onehots)
-                output_hiddens.append(paddle.unsqueeze(outputs, axis=1))
+                output_hiddens[:, i, :] = outputs
+                # output_hiddens.append(paddle.unsqueeze(outputs, axis=1))
                 structure_probs_step = self.structure_generator(outputs)
                 temp_elem = structure_probs_step.argmax(axis=1, dtype="int32")
-                i += 1
 
-            output = paddle.concat(output_hiddens, axis=1)
+            output = output_hiddens
             structure_probs = self.structure_generator(output)
             structure_probs = F.softmax(structure_probs)
-            if self.loc_type == 1:
-                loc_preds = self.loc_generator(output)
-                loc_preds = F.sigmoid(loc_preds)
-            else:
-                loc_fea = fea.transpose([0, 2, 1])
-                loc_fea = self.loc_fea_trans(loc_fea)
-                loc_fea = loc_fea.transpose([0, 2, 1])
-                loc_concat = paddle.concat([output, loc_fea], axis=2)
-                loc_preds = self.loc_generator(loc_concat)
-                loc_preds = F.sigmoid(loc_preds)
+            loc_fea = fea.transpose([0, 2, 1])
+            loc_fea = self.loc_fea_trans(loc_fea)
+            loc_fea = loc_fea.transpose([0, 2, 1])
+            loc_concat = paddle.concat([output, loc_fea], axis=2)
+            loc_preds = self.loc_generator(loc_concat)
+            loc_preds = F.sigmoid(loc_preds)
         return {'structure_probs': structure_probs, 'loc_preds': loc_preds}
 
 

test_tipc/configs/en_table_structure/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt

@@ -0,0 +1,17 @@
+===========================paddle2onnx_params===========================
+model_name:en_table_structure
+python:python3.7
+2onnx: paddle2onnx
+--det_model_dir:./inference/en_ppocr_mobile_v2.0_table_structure_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--det_save_file:./inference/en_ppocr_mobile_v2.0_table_structure_infer/model.onnx
+--rec_model_dir:
+--rec_save_file:
+--opset_version:10
+--enable_onnx_checker:True
+inference:ppstructure/table/predict_structure.py --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt
+--use_gpu:True|False
+--det_model_dir:
+--rec_model_dir:
+--image_dir:./ppstructure/docs/table/table.jpg

test_tipc/configs/layoutxlm_ser/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt

@@ -13,7 +13,7 @@ train_infer_img_dir:ppstructure/docs/kie/input/zh_val_42.jpg
 null:null
 ##
 trainer:norm_train
-norm_train:tools/train.py -c test_tipc/configs/layoutxlm_ser/ser_layoutxlm_xfund_zh.yml
+norm_train:tools/train.py -c test_tipc/configs/layoutxlm_ser/ser_layoutxlm_xfund_zh.yml -o
 pact_train:null
 fpgm_train:null
 distill_train:null

test_tipc/configs/slanet/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt

@@ -0,0 +1,17 @@
+===========================paddle2onnx_params===========================
+model_name:slanet
+python:python3.7
+2onnx: paddle2onnx
+--det_model_dir:./inference/ch_ppstructure_mobile_v2.0_SLANet_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--det_save_file:./inference/ch_ppstructure_mobile_v2.0_SLANet_infer/model.onnx
+--rec_model_dir:
+--rec_save_file:
+--opset_version:10
+--enable_onnx_checker:True
+inference:ppstructure/table/predict_structure.py --table_char_dict_path=./ppocr/utils/dict/table_structure_dict_ch.txt
+--use_gpu:True|False
+--det_model_dir:
+--rec_model_dir:
+--image_dir:./ppstructure/docs/table/table.jpg

test_tipc/configs/slanet/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt

@@ -0,0 +1,53 @@
+===========================train_params===========================
+model_name:slanet
+python:python3.7
+gpu_list:192.168.0.1,192.168.0.2;0,1
+Global.use_gpu:True
+Global.auto_cast:fp32
+Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50
+Global.save_model_dir:./output/
+Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
+Global.pretrained_model:./pretrain_models/en_ppstructure_mobile_v2.0_SLANet_train/best_accuracy
+train_model_name:latest
+train_infer_img_dir:./ppstructure/docs/table/table.jpg
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c test_tipc/configs/slanet/SLANet.yml -o
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:null
+null:null
+##
+===========================infer_params===========================
+Global.save_inference_dir:./output/
+Global.checkpoints:
+norm_export:tools/export_model.py -c test_tipc/configs/slanet/SLANet.yml -o
+quant_export:
+fpgm_export: 
+distill_export:null
+export1:null
+export2:null
+##
+infer_model:./inference/en_ppstructure_mobile_v2.0_SLANet_train
+infer_export:null
+infer_quant:False
+inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer  --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table
+--use_gpu:True|False
+--enable_mkldnn:False
+--cpu_threads:6
+--rec_batch_num:1
+--use_tensorrt:False
+--precision:fp32
+--table_model_dir:
+--image_dir:./ppstructure/docs/table/table.jpg
+null:null
+--benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,488,488]}]

test_tipc/prepare.sh

@@ -700,10 +700,18 @@ if [ ${MODE} = "cpp_infer" ];then
         wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar  --no-check-certificate
         cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_PP-OCRv3_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../
     elif [[ ${model_name} =~ "en_table_structure" ]];then
-        wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar --no-check-certificate
         wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar --no-check-certificate
         wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar --no-check-certificate
-        cd ./inference/ && tar xf en_ppocr_mobile_v2.0_table_structure_infer.tar && tar xf en_ppocr_mobile_v2.0_table_det_infer.tar && tar xf en_ppocr_mobile_v2.0_table_rec_infer.tar && cd ../
+
+        cd ./inference/ && tar xf en_ppocr_mobile_v2.0_table_det_infer.tar && tar xf en_ppocr_mobile_v2.0_table_rec_infer.tar
+        if [ ${model_name} == "en_table_structure" ]; then
+            wget -nc https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar --no-check-certificate
+            tar xf en_ppocr_mobile_v2.0_table_structure_infer.tar
+        elif [ ${model_name} == "en_table_structure_PACT" ]; then
+            wget -nc https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_slim_infer.tar --no-check-certificate
+            tar xf en_ppocr_mobile_v2.0_table_structure_slim_infer.tar
+        fi
+        cd ../
     elif [[ ${model_name} =~ "slanet" ]];then
         wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_infer.tar --no-check-certificate
         wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate
@@ -791,6 +799,12 @@ if [ ${MODE} = "paddle2onnx_infer" ];then
         wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate
         wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar --no-check-certificate
         cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_PP-OCRv3_rec_infer.tar && cd ../
+    elif [[ ${model_name} =~ "slanet" ]];then
+        wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_infer.tar --no-check-certificate
+        cd ./inference/ && tar xf ch_ppstructure_mobile_v2.0_SLANet_infer.tar && cd ../
+    elif [[ ${model_name} =~ "en_table_structure" ]];then
+        wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar --no-check-certificate
+        cd ./inference/ && tar xf en_ppocr_mobile_v2.0_table_structure_infer.tar && cd ../
     fi
     
     # wget data

test_tipc/test_paddle2onnx.sh

@@ -105,6 +105,19 @@ function func_paddle2onnx(){
         eval $trans_model_cmd
         last_status=${PIPESTATUS[0]}
         status_check $last_status "${trans_model_cmd}" "${status_log}" "${model_name}" "${trans_rec_log}"
+    elif [ ${model_name} = "slanet" ] || [ ${model_name} = "en_table_structure" ]; then
+        # trans det
+        set_dirname=$(func_set_params "--model_dir" "${det_infer_model_dir_value}")
+        set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}")
+        set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}")
+        set_save_model=$(func_set_params "--save_file" "${det_save_file_value}")
+        set_opset_version=$(func_set_params "${opset_version_key}" "${opset_version_value}")
+        set_enable_onnx_checker=$(func_set_params "${enable_onnx_checker_key}" "${enable_onnx_checker_value}")
+        trans_det_log="${LOG_PATH}/trans_model_det.log"
+        trans_model_cmd="${padlle2onnx_cmd} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_save_model} ${set_opset_version} ${set_enable_onnx_checker} --enable_dev_version=True > ${trans_det_log} 2>&1 "
+        eval $trans_model_cmd
+        last_status=${PIPESTATUS[0]}
+        status_check $last_status "${trans_model_cmd}" "${status_log}" "${model_name}" "${trans_det_log}" 
     fi
 
     # python inference
@@ -117,7 +130,7 @@ function func_paddle2onnx(){
                 set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}")
                 set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}")
                 infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 "
-            elif [[ ${model_name} =~ "det" ]]; then
+            elif [[ ${model_name} =~ "det" ]] || [ ${model_name} = "slanet" ] || [ ${model_name} = "en_table_structure" ]; then
                 set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}")
                 infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 "
             elif [[ ${model_name} =~ "rec" ]]; then
@@ -136,7 +149,7 @@ function func_paddle2onnx(){
                 set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}")
                 set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}")
                 infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 "
-            elif [[ ${model_name} =~ "det" ]]; then
+            elif [[ ${model_name} =~ "det" ]]|| [ ${model_name} = "slanet" ] || [ ${model_name} = "en_table_structure" ]; then
                 set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}")
                 infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 "
             elif [[ ${model_name} =~ "rec" ]]; then