!18733 fix bug retinanet and cnn_direction_model
Merge pull request !18733 from Maige/bug
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commit
7cb7a23f9b
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@ -55,13 +55,14 @@ fi
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mkdir ./train
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cp ./*.py ./train
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cp -r ./scripts ./train
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cp -r ./src ./train
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cp ./*yaml ./train
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cd ./train || exit
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echo "start training for device $DEVICE_ID"
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env > env.log
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if [ $# == 2 ]
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then
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python train.py --train_dataset_path=$PATH1 &> log &
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python train.py --train_dataset_path=$PATH1 &> train.log &
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fi
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if [ $# == 3 ]
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@ -111,6 +111,12 @@ file_format: "MINDIR"
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export_batch_size: 1
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file_name: "retinanet"
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# ======================================================================================
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# postprocess options
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result_path: ""
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img_path: ""
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img_id_file: ""
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---
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# Help description for each configuration
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enable_modelarts: "Whether training on modelarts default: False"
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@ -134,4 +140,7 @@ dataset: "Dataset, default is coco."
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device_id: "Device id, default is 0."
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file_format: "file format choices [AIR, MINDIR]"
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file_name: "output file name."
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export_batch_size: "batch size"
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export_batch_size: "batch size"
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result_path: "result file path."
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img_path: "image file path."
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img_id_file: "image id file."
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@ -16,16 +16,11 @@
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"""Evaluation for retinanet"""
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import os
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import argparse
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import numpy as np
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from PIL import Image
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from src.coco_eval import metrics
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from src.model_utils.config import config
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parser = argparse.ArgumentParser(description='retinanet evaluation')
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parser.add_argument("--result_path", type=str, required=True, help="result file path.")
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parser.add_argument("--img_path", type=str, required=True, help="image file path.")
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parser.add_argument("--img_id_file", type=str, required=True, help="image id file.")
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args = parser.parse_args()
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def get_pred(result_path, img_id):
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boxes_file = os.path.join(result_path, img_id + '_0.bin')
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@ -35,10 +30,12 @@ def get_pred(result_path, img_id):
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scores = np.fromfile(scores_file, dtype=np.float32).reshape(67995, 81)
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return boxes, scores
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def get_img_size(file_name):
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img = Image.open(file_name)
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return img.size
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def get_img_id(img_id_file):
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f = open(img_id_file)
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lines = f.readlines()
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@ -49,6 +46,7 @@ def get_img_id(img_id_file):
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return ids
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def cal_acc(result_path, img_path, img_id_file):
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ids = get_img_id(img_id_file)
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imgs = os.listdir(img_path)
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@ -70,5 +68,6 @@ def cal_acc(result_path, img_path, img_id_file):
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mAP = metrics(pred_data)
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print(f"mAP: {mAP}")
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if __name__ == '__main__':
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cal_acc(args.result_path, args.img_path, args.img_id_file)
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cal_acc(config.result_path, config.img_path, config.img_id_file)
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