Big update

utils/export_ppyoloe.py

@@ -0,0 +1,79 @@
+import os
+import sys
+import onnx
+import paddle
+import paddle.nn as nn
+from ppdet.core.workspace import load_config, merge_config
+from ppdet.utils.check import check_version, check_config
+from ppdet.utils.cli import ArgsParser
+from ppdet.engine import Trainer
+from ppdet.slim import build_slim_model
+
+
+class DeepStreamOutput(nn.Layer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x):
+        boxes = x['bbox']
+        x['bbox_num'] = x['bbox_num'].transpose([0, 2, 1])
+        scores = paddle.max(x['bbox_num'], 2, keepdim=True)
+        classes = paddle.cast(paddle.argmax(x['bbox_num'], 2, keepdim=True), dtype='float32')
+        return paddle.concat((boxes, scores, classes), axis=2)
+
+
+def ppyoloe_export(FLAGS):
+    cfg = load_config(FLAGS.config)
+    FLAGS.opt['weights'] = FLAGS.weights
+    FLAGS.opt['exclude_nms'] = True
+    merge_config(FLAGS.opt)
+    if FLAGS.slim_config:
+        cfg = build_slim_model(cfg, FLAGS.slim_config, mode='test')
+    merge_config(FLAGS.opt)
+    check_config(cfg)
+    check_version()
+    trainer = Trainer(cfg, mode='test')
+    trainer.load_weights(cfg.weights)
+    trainer.model.eval()
+    if not os.path.exists('.tmp'):
+        os.makedirs('.tmp')
+    static_model, _ = trainer._get_infer_cfg_and_input_spec('.tmp')
+    os.system('rm -r .tmp')
+    return cfg, static_model
+
+
+def main(FLAGS):
+    paddle.set_device('cpu')
+    cfg, model = ppyoloe_export(FLAGS)
+
+    model = nn.Sequential(model, DeepStreamOutput())
+
+    img_size = [cfg.eval_height, cfg.eval_width]
+
+    onnx_input_im = {}
+    onnx_input_im['image'] = paddle.static.InputSpec(shape=[None, 3, *img_size], dtype='float32', name='image')
+    onnx_input_im['scale_factor'] = paddle.static.InputSpec(shape=[None, 2], dtype='float32', name='scale_factor')
+    onnx_output_file = cfg.filename + '.onnx'
+
+    paddle.onnx.export(model, cfg.filename, input_spec=[onnx_input_im], opset_version=FLAGS.opset)
+
+    if FLAGS.simplify:
+        import onnxsim
+        model_onnx = onnx.load(onnx_output_file)
+        model_onnx, _ = onnxsim.simplify(model_onnx)
+        onnx.save(model_onnx, onnx_output_file)
+
+
+def parse_args():
+    parser = ArgsParser()
+    parser.add_argument('-w', '--weights', required=True, help='Input weights (.pdparams) file path (required)')
+    parser.add_argument('--slim_config', default=None, type=str, help='Slim configuration file of slim method')
+    parser.add_argument('--opset', type=int, default=11, help='ONNX opset version')
+    parser.add_argument('--simplify', action='store_true', help='ONNX simplify model')
+    args = parser.parse_args()
+    return args
+
+
+if __name__ == '__main__':
+    FLAGS = parse_args()
+    sys.exit(main(FLAGS))