初始化仓库

001导出onnx模型_0.py

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+from ultralytics import YOLO
+
+'''
+    yolo官方导出的onnx模型转换为rknn模型后并不能使用.
+'''
+# 加载模型
+model = YOLO("/home/admin-root/haotian/rk3588/pytorch模型转rknn/models/yolov8m.pt")
+
+# 导出 ONNX（关键参数！）
+model.export(
+    format="onnx",
+    imgsz=(640, 640),     # 固定输入尺寸
+    opset=12,             # ONNX 算子版本 >=12
+    simplify=True,        # 简化模型
+    dynamic=False,        # 禁用动态轴
+    nms=False,            # 移除输出端的 NMS 层（RKNN 不支持）
+)
+
+# yolo导出的模型

001导出onnx模型_1.py

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+from ultralytics import YOLO
+import torch
+
+# 加载模型时禁用数据验证
+model = YOLO("/home/admin-root/haotian/rk3588/pytorch模型转rknn/models/yolov8m.pt", task="detect")
+
+# 手动设置模型为推理模式
+model.model.eval()
+
+# 导出 ONNX
+dummy_input = torch.randn(1, 3, 640, 640)
+torch.onnx.export(
+    model.model,  # 使用 model.model 访问底层 PyTorch 模型
+    dummy_input,
+    "yolov8m.onnx",
+    input_names=["input"],
+    output_names=["output"],
+    opset_version=11,
+)

002验证ONNX模型.py

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+import onnxruntime as ort
+import numpy as np
+
+sess = ort.InferenceSession("/home/admin-root/haotian/rk3588/pytorch模型转rknn/models/yolov8m.onnx")
+input_name = sess.get_inputs()[0].name
+output_name = sess.get_outputs()[0].name
+
+# 模拟输入（BCHW 格式）
+input_data = np.random.randint(0, 255, (1, 3, 640, 640), dtype=np.uint8)
+outputs = sess.run([output_name], {input_name: input_data.astype(np.float32)})
+
+print("输出形状:", outputs[0].shape)  # 应为 [1, 84, 8400]（84=80类+4坐标）

003ONNX转RKNN.py

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+from rknn.api import RKNN
+import cv2
+import numpy as np
+
+
+# 初始化 RKNN
+rknn = RKNN()
+
+# 配置参数（关键！）
+rknn.config(
+    target_platform="rk3588",          # 根据实际芯片型号修改
+    mean_values=[[0, 0, 0]],       # YOLOv8 输入为 0-255，无需归一化
+    std_values=[[255, 255, 255]],  # 输入数据除以 255（即 0-1 范围）
+    # quant_img_RGB2BGR=True,
+    optimization_level=3,          # 最高优化级别
+)
+
+# 加载 ONNX
+ret = rknn.load_onnx(model="/home/admin-root/haotian/rk3588/pytorch模型转rknn/models/yolov8m.onnx")
+assert ret == 0, "加载 ONNX 失败！"
+
+# 转换模型
+ret = rknn.build(
+    do_quantization=False,          # 启用量化
+    # dataset="dataset.txt",         # 校准数据路径
+)
+assert ret == 0, "转换 RKNN 失败！"
+
+# 导出 RKNN
+ret = rknn.export_rknn("/home/admin-root/haotian/rk3588/pytorch模型转rknn/models/yolov8m.rknn")
+assert ret == 0, "导出 RKNN 失败！"
+
+
+# Set inputs
+img = cv2.imread('/home/admin-root/haotian/rk3588/pytorch模型转rknn/images/bus.jpg')
+img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+img.resize((3, 640, 640))
+img = np.expand_dims(img, 0)
+
+# Init runtime environment
+print('--> Init runtime environment')
+ret = rknn.init_runtime()
+if ret != 0:
+    print('Init runtime environment failed!')
+    exit(ret)
+print('done')
+
+# Inference
+print('--> Running model')
+outputs = rknn.inference(inputs=[img], data_format=['nchw'])
+np.save('./tflite_mobilenet_v1_0.npy', outputs[0])
+print(len(outputs))
+print('done')
+
+rknn.release()
+
+
+

004验证RKNN模型.py

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+
+from rknn.api import RKNN
+import cv2
+import numpy as np
+
+# Create RKNN object
+rknn = RKNN(verbose=True)
+
+# Pre-process config
+print('--> Config model')
+rknn.config(mean_values=[128, 128, 128], std_values=[128, 128, 128], target_platform='rk3566')
+print('done')
+
+# Load model (from https://www.tensorflow.org/lite/guide/hosted_models?hl=zh-cn)
+print('--> Loading model')
+ret = rknn.load_tflite(model='mobilenet_v1_1.0_224.tflite')
+if ret != 0:
+    print('Load model failed!')
+    exit(ret)
+print('done')
+
+# Build model
+print('--> Building model')
+ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
+if ret != 0:
+    print('Build model failed!')
+    exit(ret)
+print('done')
+
+# Export rknn model
+print('--> Export rknn model')
+ret = rknn.export_rknn('./mobilenet_v1.rknn')
+if ret != 0:
+    print('Export rknn model failed!')
+    exit(ret)
+print('done')
+
+# Set inputs
+img = cv2.imread('./dog_224x224.jpg')
+img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+img = np.expand_dims(img, 0)
+
+# Init runtime environment
+print('--> Init runtime environment')
+ret = rknn.init_runtime()
+if ret != 0:
+    print('Init runtime environment failed!')
+    exit(ret)
+print('done')
+
+# Inference
+print('--> Running model')
+outputs = rknn.inference(inputs=[img], data_format=['nhwc'])
+np.save('./tflite_mobilenet_v1_0.npy', outputs[0])
+show_outputs(outputs)
+print('done')
+
+rknn.release()

005推理.py

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+import cv2
+import numpy as np
+from rknnlite import RKNNLite
+
+# 初始化 RKNN
+rknn = RKNNLite()
+rknn.load_rknn("yolov8n.rknn")
+rknn.init_runtime(core_mask=RKNNLite.NPU_CORE_0)
+
+def preprocess(image):
+    # 调整尺寸并转换为 BCHW 格式
+    img = cv2.resize(image, (640, 640))
+    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)  # BGR 转 RGB（根据模型配置）
+    img = img.transpose(2, 0, 1)[np.newaxis, ...].astype(np.uint8)  # HWC -> BCHW
+    return img
+
+# 加载测试图像
+img = cv2.imread("test.jpg")
+input_data = preprocess(img)
+
+# 推理
+outputs = rknn.inference(inputs=[input_data])[0]  # 输出形状 [1, 84, 8400]
+
+# 后处理（示例：提取检测框）
+def postprocess(output, conf_thresh=0.5):
+    # 输出格式: [batch, 84, 8400]
+    # 84 = 4（坐标） + 80（类别）
+    boxes = []
+    for i in range(output.shape[2]):
+        scores = output[0, 4:84, i]
+        class_id = np.argmax(scores)
+        confidence = scores[class_id]
+        if confidence > conf_thresh:
+            cx, cy, w, h = output[0, :4, i]
+            # 转换为 x1,y1,x2,y2 格式
+            x1 = int((cx - w/2) * 640)
+            y1 = int((cy - h/2) * 640)
+            x2 = int((cx + w/2) * 640)
+            y2 = int((cy + h/2) * 640)
+            boxes.append([x1, y1, x2, y2, confidence, class_id])
+    return boxes
+
+# 执行后处理
+detections = postprocess(outputs)
+print("检测结果:", detections)
+
+rknn.release()

runs/detect/train/args.yaml

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+task: detect
+mode: train
+model: /home/admin-root/haotian/rk3588/pytorch模型转rknn/models/yolov8m.pt
+data: coco.yaml
+epochs: 100
+time: null
+patience: 100
+batch: 16
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device: null
+workers: 8
+project: null
+name: train
+exist_ok: false
+pretrained: true
+optimizer: auto
+verbose: true
+seed: 0
+deterministic: true
+single_cls: false
+rect: false
+cos_lr: false
+close_mosaic: 10
+resume: false
+amp: true
+fraction: 1.0
+profile: false
+freeze: null
+multi_scale: false
+overlap_mask: true
+mask_ratio: 4
+dropout: 0.0
+val: true
+split: val
+save_json: false
+conf: null
+iou: 0.7
+max_det: 300
+half: false
+dnn: false
+plots: true
+source: null
+vid_stride: 1
+stream_buffer: false
+visualize: false
+augment: false
+agnostic_nms: false
+classes: null
+retina_masks: false
+embed: null
+show: false
+save_frames: false
+save_txt: false
+save_conf: false
+save_crop: false
+show_labels: true
+show_conf: true
+show_boxes: true
+line_width: null
+format: torchscript
+keras: false
+optimize: false
+int8: false
+dynamic: false
+simplify: true
+opset: null
+workspace: null
+nms: false
+lr0: 0.01
+lrf: 0.01
+momentum: 0.937
+weight_decay: 0.0005
+warmup_epochs: 3.0
+warmup_momentum: 0.8
+warmup_bias_lr: 0.1
+box: 7.5
+cls: 0.5
+dfl: 1.5
+pose: 12.0
+kobj: 1.0
+nbs: 64
+hsv_h: 0.015
+hsv_s: 0.7
+hsv_v: 0.4
+degrees: 0.0
+translate: 0.1
+scale: 0.5
+shear: 0.0
+perspective: 0.0
+flipud: 0.0
+fliplr: 0.5
+bgr: 0.0
+mosaic: 1.0
+mixup: 0.0
+copy_paste: 0.0
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.4
+cfg: null
+tracker: botsort.yaml
+save_dir: runs/detect/train

runs/detect/train2/args.yaml

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+task: detect
+mode: train
+model: /home/admin-root/haotian/rk3588/pytorch模型转rknn/models/yolov8m.pt
+data: coco.yaml
+epochs: 100
+time: null
+patience: 100
+batch: 16
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device: null
+workers: 8
+project: null
+name: train2
+exist_ok: false
+pretrained: true
+optimizer: auto
+verbose: true
+seed: 0
+deterministic: true
+single_cls: false
+rect: false
+cos_lr: false
+close_mosaic: 10
+resume: false
+amp: true
+fraction: 1.0
+profile: false
+freeze: null
+multi_scale: false
+overlap_mask: true
+mask_ratio: 4
+dropout: 0.0
+val: true
+split: val
+save_json: false
+conf: null
+iou: 0.7
+max_det: 300
+half: false
+dnn: false
+plots: true
+source: null
+vid_stride: 1
+stream_buffer: false
+visualize: false
+augment: false
+agnostic_nms: false
+classes: null
+retina_masks: false
+embed: null
+show: false
+save_frames: false
+save_txt: false
+save_conf: false
+save_crop: false
+show_labels: true
+show_conf: true
+show_boxes: true
+line_width: null
+format: torchscript
+keras: false
+optimize: false
+int8: false
+dynamic: false
+simplify: true
+opset: null
+workspace: null
+nms: false
+lr0: 0.01
+lrf: 0.01
+momentum: 0.937
+weight_decay: 0.0005
+warmup_epochs: 3.0
+warmup_momentum: 0.8
+warmup_bias_lr: 0.1
+box: 7.5
+cls: 0.5
+dfl: 1.5
+pose: 12.0
+kobj: 1.0
+nbs: 64
+hsv_h: 0.015
+hsv_s: 0.7
+hsv_v: 0.4
+degrees: 0.0
+translate: 0.1
+scale: 0.5
+shear: 0.0
+perspective: 0.0
+flipud: 0.0
+fliplr: 0.5
+bgr: 0.0
+mosaic: 1.0
+mixup: 0.0
+copy_paste: 0.0
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.4
+cfg: null
+tracker: botsort.yaml
+save_dir: runs/detect/train2

runs/detect/train3/args.yaml

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+task: detect
+mode: train
+model: /home/admin-root/haotian/rk3588/pytorch模型转rknn/models/yolov8m.pt
+data: coco.yaml
+epochs: 100
+time: null
+patience: 100
+batch: 16
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device: null
+workers: 8
+project: null
+name: train3
+exist_ok: false
+pretrained: true
+optimizer: auto
+verbose: true
+seed: 0
+deterministic: true
+single_cls: false
+rect: false
+cos_lr: false
+close_mosaic: 10
+resume: false
+amp: true
+fraction: 1.0
+profile: false
+freeze: null
+multi_scale: false
+overlap_mask: true
+mask_ratio: 4
+dropout: 0.0
+val: true
+split: val
+save_json: false
+conf: null
+iou: 0.7
+max_det: 300
+half: false
+dnn: false
+plots: true
+source: null
+vid_stride: 1
+stream_buffer: false
+visualize: false
+augment: false
+agnostic_nms: false
+classes: null
+retina_masks: false
+embed: null
+show: false
+save_frames: false
+save_txt: false
+save_conf: false
+save_crop: false
+show_labels: true
+show_conf: true
+show_boxes: true
+line_width: null
+format: torchscript
+keras: false
+optimize: false
+int8: false
+dynamic: false
+simplify: true
+opset: null
+workspace: null
+nms: false
+lr0: 0.01
+lrf: 0.01
+momentum: 0.937
+weight_decay: 0.0005
+warmup_epochs: 3.0
+warmup_momentum: 0.8
+warmup_bias_lr: 0.1
+box: 7.5
+cls: 0.5
+dfl: 1.5
+pose: 12.0
+kobj: 1.0
+nbs: 64
+hsv_h: 0.015
+hsv_s: 0.7
+hsv_v: 0.4
+degrees: 0.0
+translate: 0.1
+scale: 0.5
+shear: 0.0
+perspective: 0.0
+flipud: 0.0
+fliplr: 0.5
+bgr: 0.0
+mosaic: 1.0
+mixup: 0.0
+copy_paste: 0.0
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.4
+cfg: null
+tracker: botsort.yaml
+save_dir: runs/detect/train3

runs/detect/train4/args.yaml

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+task: detect
+mode: train
+model: /home/admin-root/haotian/rk3588/pytorch模型转rknn/models/yolov8m.pt
+data: coco.yaml
+epochs: 100
+time: null
+patience: 100
+batch: 16
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device: null
+workers: 8
+project: null
+name: train4
+exist_ok: false
+pretrained: true
+optimizer: auto
+verbose: true
+seed: 0
+deterministic: true
+single_cls: false
+rect: false
+cos_lr: false
+close_mosaic: 10
+resume: false
+amp: true
+fraction: 1.0
+profile: false
+freeze: null
+multi_scale: false
+overlap_mask: true
+mask_ratio: 4
+dropout: 0.0
+val: true
+split: val
+save_json: false
+conf: null
+iou: 0.7
+max_det: 300
+half: false
+dnn: false
+plots: true
+source: null
+vid_stride: 1
+stream_buffer: false
+visualize: false
+augment: false
+agnostic_nms: false
+classes: null
+retina_masks: false
+embed: null
+show: false
+save_frames: false
+save_txt: false
+save_conf: false
+save_crop: false
+show_labels: true
+show_conf: true
+show_boxes: true
+line_width: null
+format: torchscript
+keras: false
+optimize: false
+int8: false
+dynamic: false
+simplify: true
+opset: null
+workspace: null
+nms: false
+lr0: 0.01
+lrf: 0.01
+momentum: 0.937
+weight_decay: 0.0005
+warmup_epochs: 3.0
+warmup_momentum: 0.8
+warmup_bias_lr: 0.1
+box: 7.5
+cls: 0.5
+dfl: 1.5
+pose: 12.0
+kobj: 1.0
+nbs: 64
+hsv_h: 0.015
+hsv_s: 0.7
+hsv_v: 0.4
+degrees: 0.0
+translate: 0.1
+scale: 0.5
+shear: 0.0
+perspective: 0.0
+flipud: 0.0
+fliplr: 0.5
+bgr: 0.0
+mosaic: 1.0
+mixup: 0.0
+copy_paste: 0.0
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.4
+cfg: null
+tracker: botsort.yaml
+save_dir: runs/detect/train4