From 66ec9ff2cdb113df20fb59b6a0fadd3a0c39ba2e Mon Sep 17 00:00:00 2001 From: zbl Date: Wed, 22 Oct 2025 17:01:06 +0800 Subject: [PATCH 1/9] add yoloworld --- .../contrib/cv/detection/YoloWorld/README.md | 0 .../cv/detection/YoloWorld/adapt-diff.patch | 140 ++++++++++++++++++ .../contrib/cv/detection/YoloWorld/infer.py | 23 +++ .../detection/YoloWorld/performance_test.py | 120 +++++++++++++++ .../cv/detection/YoloWorld/requirements.txt | 3 + 5 files changed, 286 insertions(+) create mode 100644 ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md create mode 100644 ACL_PyTorch/contrib/cv/detection/YoloWorld/adapt-diff.patch create mode 100644 ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py create mode 100644 ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py create mode 100644 ACL_PyTorch/contrib/cv/detection/YoloWorld/requirements.txt diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md b/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md new file mode 100644 index 0000000000..e69de29bb2 diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/adapt-diff.patch b/ACL_PyTorch/contrib/cv/detection/YoloWorld/adapt-diff.patch new file mode 100644 index 0000000000..11dc1f1733 --- /dev/null +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/adapt-diff.patch @@ -0,0 +1,140 @@ +diff --git a/ultralytics/engine/predictor.py b/ultralytics/engine/predictor.py +index b96c66e60..193e9bb8c 100644 +--- a/ultralytics/engine/predictor.py ++++ b/ultralytics/engine/predictor.py +@@ -41,6 +41,7 @@ from typing import Any, Dict, List, Optional, Union + import cv2 + import numpy as np + import torch ++from torch import nn + + from ultralytics.cfg import get_cfg, get_save_dir + from ultralytics.data import load_inference_source +@@ -179,7 +180,16 @@ class BasePredictor: + if self.args.visualize and (not self.source_type.tensor) + else False + ) +- return self.model(im, augment=self.args.augment, visualize=visualize, embed=self.args.embed, *args, **kwargs) ++ _, _, height, width = im.shape ++ img_ht, img_wt = max(height, width), max(height, width) ++ left_pad = (img_wt - width) // 2 ++ right_pad = img_wt - width - left_pad ++ top_pad = (img_ht - height) // 2 ++ bot_pad = img_ht - height - top_pad ++ im = nn.ReplicationPad2d(padding=(left_pad, right_pad, top_pad, bot_pad))(im) ++ with torch.autocast(device_type="npu",dtype=torch.float16): ++ return self.model(im, augment=self.args.augment, visualize=visualize, embed=self.args.embed, *args, **kwargs) ++ # return self.model(im, augment=self.args.augment, visualize=visualize, embed=self.args.embed, *args, **kwargs) + + def pre_transform(self, im: List[np.ndarray]) -> List[np.ndarray]: + """ +diff --git a/ultralytics/engine/validator.py b/ultralytics/engine/validator.py +index 59a4bfd1c..4d87e7a74 100644 +--- a/ultralytics/engine/validator.py ++++ b/ultralytics/engine/validator.py +@@ -156,7 +156,8 @@ class BaseValidator: + callbacks.add_integration_callbacks(self) + model = AutoBackend( + weights=model or self.args.model, +- device=select_device(self.args.device, self.args.batch), ++ # device=select_device(self.args.device, self.args.batch), ++ device=torch.device("npu"), + dnn=self.args.dnn, + data=self.args.data, + fp16=self.args.half, +diff --git a/ultralytics/nn/autobackend.py b/ultralytics/nn/autobackend.py +index eca996dc6..c56ce9901 100644 +--- a/ultralytics/nn/autobackend.py ++++ b/ultralytics/nn/autobackend.py +@@ -12,6 +12,9 @@ import cv2 + import numpy as np + import torch + import torch.nn as nn ++import torch_npu ++import torchair ++from torch_npu.contrib import transfer_to_npu + from PIL import Image + + from ultralytics.utils import ARM64, IS_JETSON, LINUX, LOGGER, PYTHON_VERSION, ROOT, YAML +@@ -204,6 +207,10 @@ class AutoBackend(nn.Module): + model.half() if fp16 else model.float() + ch = model.yaml.get("channels", 3) + self.model = model # explicitly assign for to(), cpu(), cuda(), half() ++ _config = torchair.CompilerConfig() ++ _config.experimental_config.frozen_parameter = True ++ npu_backend = torchair.get_npu_backend(compiler_config=_config) ++ model = torch.compile(model, backend=npu_backend, fullgraph=True, dynamic=False) + pt = True + + # PyTorch +diff --git a/ultralytics/nn/modules/block.py b/ultralytics/nn/modules/block.py +index 78ce2b745..0fa586dd6 100644 +--- a/ultralytics/nn/modules/block.py ++++ b/ultralytics/nn/modules/block.py +@@ -702,7 +702,12 @@ class C2fAttn(nn.Module): + (torch.Tensor): Output tensor after processing. + """ + y = list(self.cv1(x).split((self.c, self.c), 1)) +- y.extend(m(y[-1]) for m in self.m) ++ #--------------------------- ++ for lm in self.m: ++ o1 = lm(y[-1]) ++ y.extend(o1.unsqueeze(0)) ++ #--------------------------- ++ # y.extend(m(y[-1]) for m in self.m) + y.append(self.attn(y[-1], guide)) + return self.cv2(torch.cat(y, 1)) + +diff --git a/ultralytics/nn/modules/head.py b/ultralytics/nn/modules/head.py +index 52d824063..051ca9665 100644 +--- a/ultralytics/nn/modules/head.py ++++ b/ultralytics/nn/modules/head.py +@@ -160,9 +160,16 @@ class Detect(nn.Module): + # Inference path + shape = x[0].shape # BCHW + x_cat = torch.cat([xi.view(shape[0], self.no, -1) for xi in x], 2) ++ ''' + if self.format != "imx" and (self.dynamic or self.shape != shape): + self.anchors, self.strides = (x.transpose(0, 1) for x in make_anchors(x, self.stride, 0.5)) + self.shape = shape ++ ''' ++ #------------------------------------------ ++ anchors, strides = make_anchors(x, self.stride, 0.5) ++ anchors = anchors.transpose(0, 1) ++ strides = strides.transpose(0, 1) ++ #------------------------------------------ + + if self.export and self.format in {"saved_model", "pb", "tflite", "edgetpu", "tfjs"}: # avoid TF FlexSplitV ops + box = x_cat[:, : self.reg_max * 4] +@@ -176,10 +183,15 @@ class Detect(nn.Module): + grid_h = shape[2] + grid_w = shape[3] + grid_size = torch.tensor([grid_w, grid_h, grid_w, grid_h], device=box.device).reshape(1, 4, 1) +- norm = self.strides / (self.stride[0] * grid_size) +- dbox = self.decode_bboxes(self.dfl(box) * norm, self.anchors.unsqueeze(0) * norm[:, :2]) ++ # norm = self.strides / (self.stride[0] * grid_size) ++ # dbox = self.decode_bboxes(self.dfl(box) * norm, self.anchors.unsqueeze(0) * norm[:, :2]) ++ #--------------------------- ++ norm = strides / (strides[0] * grid_size) ++ dbox = self.decode_bboxes(self.dfl(box) * norm, anchors.unsqueeze(0) * norm[:, :2]) ++ #--------------------------- + else: +- dbox = self.decode_bboxes(self.dfl(box), self.anchors.unsqueeze(0)) * self.strides ++ # dbox = self.decode_bboxes(self.dfl(box), self.anchors.unsqueeze(0)) * self.strides ++ dbox = self.decode_bboxes(self.dfl(box), anchors.unsqueeze(0)) * strides + if self.export and self.format == "imx": + return dbox.transpose(1, 2), cls.sigmoid().permute(0, 2, 1) + return torch.cat((dbox, cls.sigmoid()), 1) +diff --git a/ultralytics/utils/tal.py b/ultralytics/utils/tal.py +index 3a2091f66..ed8ba55a0 100644 +--- a/ultralytics/utils/tal.py ++++ b/ultralytics/utils/tal.py +@@ -375,7 +375,8 @@ def make_anchors(feats, strides, grid_cell_offset=0.5): + sy = torch.arange(end=h, device=device, dtype=dtype) + grid_cell_offset # shift y + sy, sx = torch.meshgrid(sy, sx, indexing="ij") if TORCH_1_10 else torch.meshgrid(sy, sx) + anchor_points.append(torch.stack((sx, sy), -1).view(-1, 2)) +- stride_tensor.append(torch.full((h * w, 1), stride, dtype=dtype, device=device)) ++ #stride_tensor.append(torch.full((h * w, 1), stride, dtype=dtype, device=device)) ++ stride_tensor.append(torch.ones((h * w, 1), dtype=dtype, device=device) * stride) + return torch.cat(anchor_points), torch.cat(stride_tensor) + diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py new file mode 100644 index 0000000000..649f25a32a --- /dev/null +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py @@ -0,0 +1,23 @@ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the BSD 3-Clause License (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://opensource.org/licenses/BSD-3-Clause +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + + +from ultralytics import YOLO + +# Create a YOLO-World model +model = YOLO("yolov8s-world.pt") # or select yolov8m/l-world.pt for different sizes + +# Conduct model validation on the COCO8 example dataset +metrics = model.val(data="coco8.yaml") \ No newline at end of file diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py new file mode 100644 index 0000000000..91b9182389 --- /dev/null +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py @@ -0,0 +1,120 @@ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the BSD 3-Clause License (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://opensource.org/licenses/BSD-3-Clause +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + +import os +from ultralytics import YOLO +import time +import numpy as np +from pathlib import Path + +os.environ['TASK_QUEUE_ENABLE'] = '2' +os.environ['PYTORCH_NPU_ALLOC_CONF']='expandable_segments:True' +os.environ['HOST_CACHE_CAPACITY']='20' +os.environ['ACLNN_CACHE_LIMIT']='100000' +os.environ['ASCEND_ENHANCE_enable']='1' +os.environ["CPU_AFFINITY_CONF"] = '1' + + + +def test_yolo_world(model_path, data_path, img_size=640, conf_threshold=0.25, iou_threshold=0.5): + """ + 测试YOLO-World模型的性能和精度 + + 参数: + model_path: 模型权重文件路径 + data_path: 测试数据集配置文件路径 + img_size: 输入图像尺寸 + conf_threshold: 置信度阈值 + iou_threshold: IOU阈值 + """ + print("="*50) + print(f"开始测试YOLO-World模型: {Path(model_path).name}") + print(f"测试数据集: {Path(data_path).name}") + print(f"图像尺寸: {img_size}, 置信度阈值: {conf_threshold}, IOU阈值: {iou_threshold}") + print("="*50) + + # 加载模型 + start_load = time.time() + model = YOLO(model_path).to('npu') + load_time = time.time() - start_load + print(f"模型加载时间: {load_time:.4f}秒") + + # 精度测试 (使用val方法) + print("\n开始精度测试...") + start_val = time.time() + metrics = model.val( + data=data_path, + imgsz=img_size, + conf=conf_threshold, + iou=iou_threshold, + verbose=False # 关闭详细输出，避免冗余 + + ) + val_time = time.time() - start_val + print(f"精度测试完成，耗时: {val_time:.4f}秒") + + # 打印精度指标 + print("\n===== 精度指标 =====") + print(f"mAP@0.5: {metrics.box.map50:.4f}") + print(f"mAP@0.5:0.95: {metrics.box.map:.4f}") + print(f"P (Precision): {metrics.box.mp:.4f}") + print(f"R (Recall): {metrics.box.mr:.4f}") + + # 性能测试 (推理速度) + print("\n开始性能测试...") + # 创建测试图像 (随机像素，模拟输入) + test_image = np.random.randint(0, 255, (img_size, img_size, 3), dtype=np.uint8) + + # 预热模型 (首次推理通常较慢) + for _ in range(10): + model(test_image, imgsz=img_size, conf=conf_threshold, iou=iou_threshold, verbose=False) + + # 正式测试 + num_runs = 100 # 测试次数 + start_infer = time.time() + for _ in range(num_runs): + model(test_image, imgsz=img_size, conf=conf_threshold, iou=iou_threshold, verbose=False) + infer_time = time.time() - start_infer + + # 计算性能指标 + avg_infer_time = infer_time / num_runs * 1000 # 转换为毫秒 + fps = num_runs / infer_time + + # 打印性能指标 + print("\n===== 性能指标 =====") + print(f"平均推理时间: {avg_infer_time:.2f}毫秒") + print(f"帧率 (FPS): {fps:.2f}") + print("\n" + "="*50) + print("测试完成!") + print("="*50) + +if __name__ == "__main__": + # 模型和数据集配置 + MODEL_PATH = "/root/work/filestorage/weight_models/YOLOWorld/yolov8x-worldv2.pt" # 可替换为yolov8m-world.pt或yolov8l-world.pt + DATA_PATH = "coco8.yaml" # 测试数据集配置文件 + + # 测试参数 + IMG_SIZE = 640 + CONF_THRESHOLD = 0.25 + IOU_THRESHOLD = 0.5 + + # 执行测试 + test_yolo_world( + model_path=MODEL_PATH, + data_path=DATA_PATH, + img_size=IMG_SIZE, + conf_threshold=CONF_THRESHOLD, + iou_threshold=IOU_THRESHOLD + ) \ No newline at end of file diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/requirements.txt b/ACL_PyTorch/contrib/cv/detection/YoloWorld/requirements.txt new file mode 100644 index 0000000000..755adf5563 --- /dev/null +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/requirements.txt @@ -0,0 +1,3 @@ +numpy==1.26.4 +opencv-python==4.9.0.80 +polars==1.33.1 \ No newline at end of file -- Gitee From 2f5a8aab8a956439f14c64f0aaf92290d1022b2d Mon Sep 17 00:00:00 2001 From: zbl Date: Wed, 22 Oct 2025 17:18:26 +0800 Subject: [PATCH 2/9] add yoloworld --- .../contrib/cv/detection/YoloWorld/README.md | 96 +++++++++++++++++++ .../detection/YoloWorld/performance_test.py | 2 +- 2 files changed, 97 insertions(+), 1 deletion(-) diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md b/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md index e69de29bb2..a46a9c4237 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md @@ -0,0 +1,96 @@ +# YoloWorld高性能(TorchAir)-推理指导 + +- [概述](#概述) +- [推理环境准备](#推理环境准备) +- [快速上手](#快速上手) + - [获取源码](#获取源码) + - [模型推理](#模型推理) +- [模型推理性能&精度](#模型推理性能&精度) + +****** + +# 概述 +YOLOWorld 是对传统 YOLO 系列的突破性扩展，通过融合文本语义解决了 “类别固定” 的痛点。 + +- 版本说明： + ``` + url=https://github.com/ultralytics/ultralytics + tag=8.3.180 + model_name=yolov8x-worldv2.pt + ``` + +# 推理环境准备 +- 该模型需要以下插件与驱动 + **表 1** 版本配套表 + + | 配套 | 版本 | 环境准备指导 | + | ------------------------------------------------------------ |--------------| ------------------------------------------------------------ | + | 固件与驱动 | 24.0.0 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | + | CANN | 8.2.rc1 | - | + | Python | 3.11 | - | + | PyTorch | 2.6.0 | - | + | Ascend Extension PyTorch | 2.6.0 | - | + | 说明：Atlas 800I A2/Atlas 300I Pro 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | + + +# 快速上手 + +## 获取源码 +1. 获取本仓源码 + + ``` + git clone https://gitee.com/ascend/ModelZoo-PyTorch.git + cd ModelZoo-PyTorch/ACL_PyTorch/contrib/cv/detection/YoloWorld + ``` + +1. 获取模型仓源码 + ```bash + git clone https://github.com/ultralytics/ultralytics.git + cd ultralytics + git checkout v8.3.180 + git apply ../adapt-diff.patch + pip install -e . + ``` + +2. 安装依赖 + ```bash + pip3 install -r requirements.txt + ``` + +3. 下载模型权重 + + 开源链接：https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8x-world.pt + 魔塔社区：https://modelscope.cn/models/anyforge/ultralytics-allmodels/files + +4. 完整下载后的文件目录树如下 + + ```shell + YoloWorld + ├── ultralytics // 从开源代码仓下载的文件夹 + ├── yolov8x-world.pt // 模型权重下载 + ├── adapt-diff.patch + ├── infer.py // 本仓库提供的自定义推理脚本 + ├── README.md + └── requirements.txt + ``` + +## 模型推理 + +1. 执行推理命令 + + ```bash + # 解决nan值导致的精度异常问题 + export INF_NAN_MODE_FORCE_DISABLE=1 + + python3 infer.py + ``` + + 推理后将打屏推理结果和模型性能 + +# 模型推理性能&精度 +以800I A2为例 + +| 模型 | 硬件 | 端到端性能 | +|---------------------|------|-------------------| +| yolov8x-worldv2 |800T A2| 69.64 FPS | + diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py index 91b9182389..a14199949c 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py @@ -102,7 +102,7 @@ def test_yolo_world(model_path, data_path, img_size=640, conf_threshold=0.25, io if __name__ == "__main__": # 模型和数据集配置 - MODEL_PATH = "/root/work/filestorage/weight_models/YOLOWorld/yolov8x-worldv2.pt" # 可替换为yolov8m-world.pt或yolov8l-world.pt + MODEL_PATH = "$HOME/yolov8x-worldv2.pt" # 可替换为yolov8m-world.pt或yolov8l-world.pt DATA_PATH = "coco8.yaml" # 测试数据集配置文件 # 测试参数 -- Gitee From d6ddfcc9b48a985de0c7dc4f4f28b3840a4ecf8e Mon Sep 17 00:00:00 2001 From: zbl Date: Wed, 22 Oct 2025 17:20:31 +0800 Subject: [PATCH 3/9] add yoloworld --- ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md | 6 +++++- .../contrib/cv/detection/YoloWorld/performance_test.py | 3 +-- 2 files changed, 6 insertions(+), 3 deletions(-) diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md b/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md index a46a9c4237..32e92c26d0 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/README.md @@ -84,7 +84,11 @@ YOLOWorld 是对传统 YOLO 系列的突破性扩展，通过融合文本语义 python3 infer.py ``` - + +2. 性能推理命令 + ```bash + python3 performance_test.py + ``` 推理后将打屏推理结果和模型性能 # 模型推理性能&精度 diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py index a14199949c..57b3b18146 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py @@ -21,9 +21,8 @@ from pathlib import Path os.environ['TASK_QUEUE_ENABLE'] = '2' os.environ['PYTORCH_NPU_ALLOC_CONF']='expandable_segments:True' -os.environ['HOST_CACHE_CAPACITY']='20' +# os.environ['HOST_CACHE_CAPACITY']='20' os.environ['ACLNN_CACHE_LIMIT']='100000' -os.environ['ASCEND_ENHANCE_enable']='1' os.environ["CPU_AFFINITY_CONF"] = '1' -- Gitee From 6ee4dfbbd5022a4748b7fcb7773cc04d5755a063 Mon Sep 17 00:00:00 2001 From: zbl Date: Wed, 22 Oct 2025 17:49:25 +0800 Subject: [PATCH 4/9] add yoloworld --- .../detection/YoloWorld/performance_test.py | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py index 57b3b18146..c947fb36c5 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py @@ -14,15 +14,16 @@ import os -from ultralytics import YOLO import time -import numpy as np from pathlib import Path +from ultralytics import YOLO +import numpy as np + os.environ['TASK_QUEUE_ENABLE'] = '2' -os.environ['PYTORCH_NPU_ALLOC_CONF']='expandable_segments:True' -# os.environ['HOST_CACHE_CAPACITY']='20' -os.environ['ACLNN_CACHE_LIMIT']='100000' +os.environ['PYTORCH_NPU_ALLOC_CONF'] = 'expandable_segments:True' +# os.environ['HOST_CACHE_CAPACITY'] = '20' +os.environ['ACLNN_CACHE_LIMIT'] = '100000' os.environ["CPU_AFFINITY_CONF"] = '1' @@ -38,11 +39,11 @@ def test_yolo_world(model_path, data_path, img_size=640, conf_threshold=0.25, io conf_threshold: 置信度阈值 iou_threshold: IOU阈值 """ - print("="*50) + print("=" * 50) print(f"开始测试YOLO-World模型: {Path(model_path).name}") print(f"测试数据集: {Path(data_path).name}") print(f"图像尺寸: {img_size}, 置信度阈值: {conf_threshold}, IOU阈值: {iou_threshold}") - print("="*50) + print("=" * 50) # 加载模型 start_load = time.time() @@ -95,9 +96,9 @@ def test_yolo_world(model_path, data_path, img_size=640, conf_threshold=0.25, io print("\n===== 性能指标 =====") print(f"平均推理时间: {avg_infer_time:.2f}毫秒") print(f"帧率 (FPS): {fps:.2f}") - print("\n" + "="*50) + print("\n" + "=" * 50) print("测试完成!") - print("="*50) + print("=" * 50) if __name__ == "__main__": # 模型和数据集配置 -- Gitee From 837f122037ccec91b55f692b1bfc60a588d012cc Mon Sep 17 00:00:00 2001 From: zbl Date: Wed, 22 Oct 2025 17:56:18 +0800 Subject: [PATCH 5/9] add yoloworld --- ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py | 1 - 1 file changed, 1 deletion(-) diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py index c947fb36c5..755564b68b 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py @@ -22,7 +22,6 @@ import numpy as np os.environ['TASK_QUEUE_ENABLE'] = '2' os.environ['PYTORCH_NPU_ALLOC_CONF'] = 'expandable_segments:True' -# os.environ['HOST_CACHE_CAPACITY'] = '20' os.environ['ACLNN_CACHE_LIMIT'] = '100000' os.environ["CPU_AFFINITY_CONF"] = '1' -- Gitee From 33519dd76728f41af29e9a0260cdddd16d022218 Mon Sep 17 00:00:00 2001 From: zbl Date: Wed, 22 Oct 2025 18:26:33 +0800 Subject: [PATCH 6/9] add yoloworld --- .../cv/detection/YoloWorld/performance_test.py | 16 ++++------------ 1 file changed, 4 insertions(+), 12 deletions(-) diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py index 755564b68b..1827391c09 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py @@ -1,10 +1,10 @@ -# Copyright 2021 Huawei Technologies Co., Ltd +# Copyright 2024 Huawei Technologies Co., Ltd # -# Licensed under the BSD 3-Clause License (the "License"); +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# https://opensource.org/licenses/BSD-3-Clause +# https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, @@ -64,12 +64,6 @@ def test_yolo_world(model_path, data_path, img_size=640, conf_threshold=0.25, io val_time = time.time() - start_val print(f"精度测试完成，耗时: {val_time:.4f}秒") - # 打印精度指标 - print("\n===== 精度指标 =====") - print(f"mAP@0.5: {metrics.box.map50:.4f}") - print(f"mAP@0.5:0.95: {metrics.box.map:.4f}") - print(f"P (Precision): {metrics.box.mp:.4f}") - print(f"R (Recall): {metrics.box.mr:.4f}") # 性能测试 (推理速度) print("\n开始性能测试...") @@ -95,9 +89,7 @@ def test_yolo_world(model_path, data_path, img_size=640, conf_threshold=0.25, io print("\n===== 性能指标 =====") print(f"平均推理时间: {avg_infer_time:.2f}毫秒") print(f"帧率 (FPS): {fps:.2f}") - print("\n" + "=" * 50) - print("测试完成!") - print("=" * 50) + if __name__ == "__main__": # 模型和数据集配置 -- Gitee From f3f44ffb6c3c1fe093212dbb3d125048ca796cac Mon Sep 17 00:00:00 2001 From: zbl Date: Wed, 22 Oct 2025 18:27:06 +0800 Subject: [PATCH 7/9] add yoloworld --- ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py index 1827391c09..b1af9368db 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py @@ -93,7 +93,7 @@ def test_yolo_world(model_path, data_path, img_size=640, conf_threshold=0.25, io if __name__ == "__main__": # 模型和数据集配置 - MODEL_PATH = "$HOME/yolov8x-worldv2.pt" # 可替换为yolov8m-world.pt或yolov8l-world.pt + MODEL_PATH = "yolov8x-worldv2.pt" # 可替换为yolov8m-world.pt或yolov8l-world.pt DATA_PATH = "coco8.yaml" # 测试数据集配置文件 # 测试参数 -- Gitee From f88adcb27c284c0516088354c1e0ce82cfa0b587 Mon Sep 17 00:00:00 2001 From: zbl Date: Wed, 22 Oct 2025 18:35:18 +0800 Subject: [PATCH 8/9] add yoloworld --- ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py | 12 ++++++------ .../cv/detection/YoloWorld/performance_test.py | 8 ++++---- 2 files changed, 10 insertions(+), 10 deletions(-) diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py index 649f25a32a..9dd8d6a1fd 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py @@ -1,11 +1,11 @@ -# Copyright 2021 Huawei Technologies Co., Ltd +# Copyright 2025 Huawei Technologies Co., Ltd # -# Licensed under the BSD 3-Clause License (the "License"); +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at -# -# https://opensource.org/licenses/BSD-3-Clause -# + +# http://www.apache.org/licenses/LICENSE-2.0 + # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. @@ -17,7 +17,7 @@ from ultralytics import YOLO # Create a YOLO-World model -model = YOLO("yolov8s-world.pt") # or select yolov8m/l-world.pt for different sizes +model = YOLO("yolov8x-worldv2.pt") # or select yolov8m/l-world.pt for different sizes # Conduct model validation on the COCO8 example dataset metrics = model.val(data="coco8.yaml") \ No newline at end of file diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py index b1af9368db..be6391b3a2 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py @@ -1,11 +1,11 @@ -# Copyright 2024 Huawei Technologies Co., Ltd +# Copyright 2025 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at -# -# https://www.apache.org/licenses/LICENSE-2.0 -# + +# http://www.apache.org/licenses/LICENSE-2.0 + # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -- Gitee From 5a3e094898dabe5e2e91b18a1ccc68a01463a10b Mon Sep 17 00:00:00 2001 From: zbl Date: Wed, 22 Oct 2025 18:41:58 +0800 Subject: [PATCH 9/9] add yoloworld --- ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py | 12 ------------ .../cv/detection/YoloWorld/performance_test.py | 12 ------------ 2 files changed, 24 deletions(-) diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py index 9dd8d6a1fd..75d84b3ee0 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/infer.py @@ -1,16 +1,4 @@ -# Copyright 2025 Huawei Technologies Co., Ltd -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# http://www.apache.org/licenses/LICENSE-2.0 - -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py index be6391b3a2..608c1e3ee6 100644 --- a/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py +++ b/ACL_PyTorch/contrib/cv/detection/YoloWorld/performance_test.py @@ -1,16 +1,4 @@ -# Copyright 2025 Huawei Technologies Co., Ltd -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# http://www.apache.org/licenses/LICENSE-2.0 - -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. import os -- Gitee