add filter

Makefile.gpu

 DATA_ROOT_DIR = /data2/ocr/outer
-REC_DATA_ROOT_DIR = /dev/data/jinlong/data
-# ['conv', 'conv-lite', 'densenet', 'densenet-lite']
+REC_DATA_ROOT_DIR = /root/jinlong/data
+# ['conv', 'conv-lite-rnn', 'densenet', 'densenet-lite']
 EMB_MODEL_TYPE = densenet-lite
-SEQ_MODEL_TYPE = lstm
+SEQ_MODEL_TYPE = gru
 MODEL_NAME = $(EMB_MODEL_TYPE)-$(SEQ_MODEL_TYPE)
-EPOCH = 20
+EPOCH = 41
 
 gen-lst:
 	python scripts/im2rec.py --list --num-label 20 --chunks 1 --train-idx-fp $(DATA_ROOT_DIR)/train.txt \
@@ -19,13 +19,19 @@ gen-rec:
 
 train:
 	nohup python scripts/cnocr_train.py --gpu 2 --emb_model_type $(EMB_MODEL_TYPE) --seq_model_type $(SEQ_MODEL_TYPE) \
-	--optimizer Adam --epoch $(EPOCH) --lr 3e-4 \
-		--train_file $(REC_DATA_ROOT_DIR)/lst/cnocr_train --test_file $(REC_DATA_ROOT_DIR)/lst/cnocr_test \
-		>> nohup-$(MODEL_NAME).out 2>&1 &
+	--optimizer Adam --epoch $(EPOCH) --lr 3e-5 --load_epoch 31 \
+	--train_file $(REC_DATA_ROOT_DIR)/lst/cnocr_train --test_file $(REC_DATA_ROOT_DIR)/lst/cnocr_test \
+	>> nohup-$(MODEL_NAME).out 2>&1 &
+
+evaluate:
+	python scripts/cnocr_evaluate.py --model-name $(MODEL_NAME) --model-epoch $(EPOCH) -i $(REC_DATA_ROOT_DIR)/test-part.txt --image-prefix-dir $(REC_DATA_ROOT_DIR) --batch-size 128 --gpu 1 -o evaluate/$(MODEL_NAME)-$(EPOCH)
+
+filter:
+	python scripts/filter_samples.py --sample_file $(REC_DATA_ROOT_DIR)/test-part.txt --badcases_file evaluate/$(MODEL_NAME)-$(EPOCH)/badcases.txt --distance_thrsh 2 -o $(REC_DATA_ROOT_DIR)/new.txt
 
 predict:
 	python scripts/cnocr_predict.py --model_name $(MODEL_NAME) --file examples/rand_cn1.png
 
 
 
-.PHONY: gen-lst gen-rec train predict
+.PHONY: gen-lst gen-rec train predict evaluate filter