yolo的分类模型不支持吗？yolov5 v8和v11的分类模型，怎么一个都没有？

[xinsuinizhuan]

yolo11n-cls的模型，自己先导出onnx，然后用如下命令导出成rnnn模型：

import sys
from rknn.api import RKNN

DATASET_PATH = './datasets/coco128'
DEFAULT_RKNN_PATH = './cls.rknn'
DEFAULT_QUANT = False

def parse_arg():
if len(sys.argv) < 3:
print("Usage: python3 {} onnx_model_path [platform] [dtype(optional)] [output_rknn_path(optional)]".format(sys.argv[0]))
print(" platform choose from [rk3562,rk3566,rk3568,rk3588,rk3576,rk1808,rv1109,rv1126]")
print(" dtype choose from [i8, fp] for [rk3562,rk3566,rk3568,rk3588,rk3576]")
print(" dtype choose from [u8, fp] for [rk1808,rv1109,rv1126]")
exit(1)

model_path = sys.argv[1]
platform = sys.argv[2]

do_quant = DEFAULT_QUANT
if len(sys.argv) > 3:
    model_type = sys.argv[3]
    if model_type not in ['i8', 'u8', 'fp']:
        print("ERROR: Invalid model type: {}".format(model_type))
        exit(1)
    elif model_type in ['i8', 'u8']:
        do_quant = True
    else:
        do_quant = False

if len(sys.argv) > 4:
    output_path = sys.argv[4]
else:
    output_path = DEFAULT_RKNN_PATH

return model_path, platform, do_quant, output_path

if name == 'main':
model_path, platform, do_quant, output_path = parse_arg()

# Create RKNN object
rknn = RKNN(verbose=False)

# Pre-process config
print('--> Config model')
rknn.config(mean_values=[[0, 0, 0]], std_values=[[255, 255, 255]], target_platform=platform)
print('done')

# Load model
print('--> Loading model')
ret = rknn.load_onnx(model=model_path, inputs=['images'], input_size_list=[[1,3,256,256]])
if ret != 0:
    print('Load model failed!')
    exit(ret)
print('done')

# Build model
print('--> Building model')
ret = rknn.build(do_quantization=do_quant, dataset=DATASET_PATH)
if ret != 0:
    print('Build model failed!')
    exit(ret)
print('done')

# Export rknn model
print('--> Export rknn model')
ret = rknn.export_rknn(output_path)
if ret != 0:
    print('Export rknn model failed!')
    exit(ret)
print('done')

# Release
rknn.release()

但是拿导出的模型去做推理时，啥也检测不到，没法分类