1

opencv-test/test/kernel.errors.txt

@@ -0,0 +1,16 @@
+Instruction / Operand / Region Errors: 
+
+/-------------------------------------------!!!KERNEL HEADER ERRORS FOUND!!!-------------------------------------------\
+Error in CISA routine with name: kernel
+                  Error Message: Input V38 = [256, 260) intersects with V37 = [256, 260)
+\----------------------------------------------------------------------------------------------------------------------/
+
+
+/-------------------------------------------!!!KERNEL HEADER ERRORS FOUND!!!-------------------------------------------\
+Error in CISA routine with name: kernel
+                  Error Message: Explicit input 2 must not follow an implicit input 0
+\----------------------------------------------------------------------------------------------------------------------/
+
+
+
+

opencv-test/x64/Release/best.xml

@@ -0,0 +1,4755 @@
+<?xml version="1.0"?>
+<net name="Model0" version="11">
+	<layers>
+		<layer id="0" name="x" type="Parameter" version="opset1">
+			<data shape="1,3,448,448" element_type="f32" />
+			<output>
+				<port id="0" precision="FP32" names="x">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>448</dim>
+					<dim>448</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="self.model.0.conv.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="16, 3, 3, 3" offset="0" size="1728" />
+			<output>
+				<port id="0" precision="FP32" names="self.model.0.conv.weight">
+					<dim>16</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="2" name="__module.model.0.conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>448</dim>
+					<dim>448</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>16</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>224</dim>
+					<dim>224</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="__module.model.0.conv/aten::_convolution/Reshape" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 16, 1, 1" offset="1728" size="64" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="__module.model.0.conv/aten::_convolution/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>224</dim>
+					<dim>224</dim>
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+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="51_1">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>224</dim>
+					<dim>224</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="__module.model.10.conv.act/aten::silu_/Swish" type="Swish" version="opset4">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>224</dim>
+					<dim>224</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="51,input.1">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>224</dim>
+					<dim>224</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="self.model.1.conv.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="32, 16, 3, 3" offset="1792" size="18432" />
+			<output>
+				<port id="0" precision="FP32" names="self.model.1.conv.weight">
+					<dim>32</dim>
+					<dim>16</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="__module.model.1.conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>224</dim>
+					<dim>224</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>32</dim>
+					<dim>16</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="__module.model.1.conv/aten::_convolution/Reshape" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 32, 1, 1" offset="20224" size="128" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="__module.model.1.conv/aten::_convolution/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="65_1">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="__module.model.10.conv.act/aten::silu_/Swish_1" type="Swish" version="opset4">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="65,input.5">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="self.model.2.cv1.conv.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="32, 32, 1, 1" offset="20352" size="4096" />
+			<output>
+				<port id="0" precision="FP32" names="self.model.2.cv1.conv.weight">
+					<dim>32</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="__module.model.2.cv1.conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>32</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="__module.model.2.cv1.conv/aten::_convolution/Reshape" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 32, 1, 1" offset="24448" size="128" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="__module.model.2.cv1.conv/aten::_convolution/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
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+					<dim>112</dim>
+					<dim>112</dim>
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+					<dim>32</dim>
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+					<dim>1</dim>
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+			</input>
+			<output>
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+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="__module.model.10.conv.act/aten::silu_/Swish_2" type="Swish" version="opset4">
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+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="71" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="24576" size="8" />
+			<output>
+				<port id="0" precision="I64" names="71" />
+			</output>
+		</layer>
+		<layer id="17" name="Constant_187" type="Const" version="opset1">
+			<data element_type="i64" shape="2" offset="24584" size="16" />
+			<output>
+				<port id="0" precision="I64" names="85">
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="__module.model.2/aten::split_with_sizes/VariadicSplit" type="VariadicSplit" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
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+				</port>
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+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="self.model.2.m.0.cv1.conv.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="8, 16, 3, 3" offset="24600" size="4608" />
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+					<dim>16</dim>
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+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="__module.model.2.m.0.cv1.conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
+			<input>
+				<port id="0" precision="FP32">
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+		</layer>
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="22" name="__module.model.2.m.0.cv1.conv/aten::_convolution/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
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+		<layer id="24" name="self.model.2.m.0.cv2.conv.weight" type="Const" version="opset1">
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+		<layer id="25" name="__module.model.2.m.0.cv2.conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
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+		<layer id="26" name="__module.model.2.m.0.cv2.conv/aten::_convolution/Reshape" type="Const" version="opset1">
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+	<rt_info>
+		<Runtime_version value="2026.0.0-20965-c6d6a13a886-releases/2026/0" />
+		<conversion_parameters>
+			<framework value="pytorch" />
+			<is_python_object value="True" />
+		</conversion_parameters>
+		<model_info>
+			<iou_threshold value="0.7" />
+			<labels value="baixiangguo biandou bingtangcheng boluo caomei chelizi fanlizhi fanshiliu fengshuili haitangguo hamigua hongmaodan hongti huangguanli huluobo huolongguo kuerlexiangli kugua lanmei liulian lizhi longyan mangguo mihoutao miju mugua nanguoli niuyouguo pingguo qicheng qiezi qingti renxinguo shanzhu shatangju shiliu tudou wandou wandoujia xiangjiao xigua xueli yali yezi yumi" />
+			<model_type value="YOLO" />
+			<pad_value value="114" />
+			<reverse_input_channels value="YES" />
+			<scale_values value="255" />
+		</model_info>
+	</rt_info>
+</net>

opencv-test/x64/Release/metadata.yaml

@@ -0,0 +1,67 @@
+description: Ultralytics YOLO26n-cls model trained on E:\code\zhipuzi\yolo\dataset-old
+author: Ultralytics
+date: '2026-03-12T14:23:44.283818'
+version: 8.4.14
+license: AGPL-3.0 License (https://ultralytics.com/license)
+docs: https://docs.ultralytics.com
+stride: 1
+task: classify
+batch: 1
+imgsz:
+- 448
+- 448
+names:
+  0: baixiangguo
+  1: biandou
+  2: bingtangcheng
+  3: boluo
+  4: caomei
+  5: chelizi
+  6: fanlizhi
+  7: fanshiliu
+  8: fengshuili
+  9: haitangguo
+  10: hamigua
+  11: hongmaodan
+  12: hongti
+  13: huangguanli
+  14: huluobo
+  15: huolongguo
+  16: kuerlexiangli
+  17: kugua
+  18: lanmei
+  19: liulian
+  20: lizhi
+  21: longyan
+  22: mangguo
+  23: mihoutao
+  24: miju
+  25: mugua
+  26: nanguoli
+  27: niuyouguo
+  28: pingguo
+  29: qicheng
+  30: qiezi
+  31: qingti
+  32: renxinguo
+  33: shanzhu
+  34: shatangju
+  35: shiliu
+  36: tudou
+  37: wandou
+  38: wandoujia
+  39: xiangjiao
+  40: xigua
+  41: xueli
+  42: yali
+  43: yezi
+  44: yumi
+args:
+  batch: 1
+  fraction: 1.0
+  half: false
+  int8: false
+  dynamic: false
+  nms: false
+channels: 3
+end2end: false