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annotate yolo_prediction.xml @ 4:e93df15bbd79 draft default tip

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author bgruening
date Mon, 21 Jul 2025 15:50:37 +0000
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1 <tool id="yolo_predict" name="Perform YOLO image labeling" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="24.2">
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2 <description>with ultralytics</description>
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3 <macros>
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4 <import>macros.xml</import>
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5 </macros>
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6 <expand macro="creator" />
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7 <expand macro="edam" />
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8 <expand macro="requirements" />
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9 <command detect_errors="aggressive">
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10 <![CDATA[
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11 export YOLO_CONFIG_DIR="\$HOME/.config/ultralytics" &&
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13 mkdir -p ./input_images ./runs ./models ./results &&
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15 #for $filename in $input_images:
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16 ln -s '$filename' './input_images/${filename.element_identifier}.${filename.ext}' &&
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17 #end for
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19 cp '$class_name' './models/class_name.txt' &&
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21 cp '$model' './models/model.pt' &&
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22
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23 python '$__tool_directory__/yolov8.py'
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24 --test_path='./input_images'
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25 --model_path='./models'
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26 --model_name='model'
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27 --run_dir='./runs'
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28 --save_dir='./results'
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29 --image_size='$image_size'
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30 --mode='$mode'
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31 --foldername='overlaid_images'
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32 --class_names_file='$class_name'
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33 --num_classes=`wc -l < ./models/class_name.txt`
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34 --confidence='$confidence'
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35 --iou='$iou'
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36 --max_det='$max_det'
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37 --headless
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38 ]]>
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39 </command>
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40 <inputs>
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41 <param name="input_images" type="data" format="jpg,png" multiple="true" label="Input images"/>
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42 <param name="class_name" type="data" format="txt" label="YOLO class name file" />
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43 <param name="model" type="data" format="data" label="Model file" />
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44 <param name="mode" type="select" label="Prediction mode">
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45 <option value="segment">segment</option>
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46 <option value="detect">detect</option>
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47 </param>
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48 <param name="image_size" type="integer" value="1000" min="16" label="Image size" help="All input images will be re-sized to squares with sides of this length (in pixels). This value governs the trade-offs of speed (smaller values) vs accuracy (larger values)." />
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49 <param name="confidence" type="float" value="0.5" min="0.0" max="1.0" label="Confidence" help="Confidence value (0-1) for each detected bounding box." />
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50 <param name="iou" type="float" value="0.7" min="0.1" max="1.0" label="IoU" help="Intersection over Union threshold for non-maximum suppression." />
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51 <param name="max_det" type="integer" value="300" min="100" max="1000" label="Max. number of detections" help="Maximum number of detections allowed per image. Limits the total number of objects the model can detect in a single inference, preventing excessive outputs in dense scenes." />
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52 </inputs>
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53 <outputs>
1
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54 <collection name="txt_results" format="txt" type="list" label="YOLO bounding box and annotation (text)">
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55 <discover_datasets pattern="(?P&lt;designation&gt;.+)\.txt$" directory="results" />
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56 </collection>
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57 <collection name="mask_results" format="tiff" type="list" label="YOLO segmentation masks (TIFF)">
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58 <filter>mode == 'segment'</filter>
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59 <discover_datasets pattern="(?P&lt;designation&gt;.+)_mask\.tiff$" directory="results" />
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60 </collection>
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61 <collection name="overlay_results" format="jpg" type="list" label="YOLO annotated images">
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62 <discover_datasets pattern="(?P&lt;designation&gt;.+)\.jpg$" directory="runs/overlaid_images" />
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63 </collection>
0
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64 </outputs>
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65 <tests>
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66 <test expect_num_outputs="3">
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67 <param name="input_images" value="pred-test01.jpg" />
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68 <param name="model" location="https://zenodo.org/records/15611468/files/best.pt" />
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69 <param name="image_size" value="512" />
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70 <param name="confidence" value="0.003" />
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71 <param name="iou" value="0.7" />
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72 <param name="max_det" value="100" />
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73 <param name="mode" value="segment" />
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74 <param name="class_name" value="class_name.txt" />
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76 <output_collection name="txt_results" type="list" count="1">
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77 <element name="pred-test01.jpg">
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78 <assert_contents>
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79 <has_n_lines n="100"/>
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80 </assert_contents>
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81 </element>
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82 </output_collection>
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84 <output_collection name="mask_results" type="list" count="1">
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85 <element name="pred-test01.jpg">
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86 <assert_contents>
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87 <has_image_width width="512"/>
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88 <has_image_height height="1024"/>
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89 <has_image_channels channels="1"/>
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90 </assert_contents>
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91 </element>
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92 </output_collection>
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93 <output_collection name="overlay_results" type="list" count="1">
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94 <element name="pred-test01.jpg">
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95 <assert_contents>
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96 <has_image_width width="512"/>
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97 <has_image_height height="1024"/>
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98 <has_image_channels channels="3"/>
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99 </assert_contents>
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100 </element>
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101 </output_collection>
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102
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103 </test>
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104 <!--new version's test-->
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105 <!-- SEGMENT MODE TEST -->
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106
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107 <test expect_num_outputs="3">
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108 <param name="input_images" value="bus.jpg" />
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109 <param name="class_name" value="yolo-test-classes.txt" />
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110 <param name="model" location="https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8n-seg.pt" />
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111 <param name="mode" value="segment" />
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112 <param name="image_size" value="640" />
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113 <param name="confidence" value="0.25" />
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114 <param name="iou" value="0.45" />
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115 <param name="max_det" value="300" />
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116 <output_collection name="txt_results" type="list" count="1">
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117 <element name="bus.jpg" file="bus.txt" compare="sim_size" />
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118 </output_collection>
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119 <output_collection name="mask_results" type="list" count="1">
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120 <element name="bus.jpg" file="bus_mask.tiff" compare="sim_size" />
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121 </output_collection>
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122 <output_collection name="overlay_results" type="list" count="1">
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123 <element name="bus.jpg" file="bus_seg.jpg" compare="sim_size" />
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124 </output_collection>
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125 </test>
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126
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127 <!-- DETECT MODE TEST -->
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128
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129 <test expect_num_outputs="2">
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130 <param name="input_images" value="bus.jpg" />
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131 <param name="class_name" value="yolo-test-classes.txt" />
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132 <param name="model" location="https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8n-seg.pt" />
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133 <param name="mode" value="detect" />
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134 <param name="image_size" value="640" />
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135 <param name="confidence" value="0.25" />
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136 <param name="iou" value="0.45" />
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137 <param name="max_det" value="300" />
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138 <output_collection name="txt_results" type="list" count="1">
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139 <element name="bus.jpg" file="bus_detect.txt" compare="sim_size" />
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140 </output_collection>
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141 <output_collection name="overlay_results" type="list" count="1">
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142 <element name="bus.jpg" file="bus_seg.jpg" compare="sim_size" />
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143 </output_collection>
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144 </test>
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145
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146 </tests>
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147
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148 <help><![CDATA[
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149 **Overview**
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150
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151 This Galaxy tool performs object detection or instance segmentation on input images using a **pre-trained YOLOv8 model** from the **Ultralytics** framework.
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152
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153 ---
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154
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155 **Prediction Mode**
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156
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157 Choose from two available options using the **mode** parameter:
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158
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159 - **detect** – Use this if your pre-trained/trained model is a detection model. It outputs bounding boxes coordinates, class IDs, and confidence scores and overlay images with bounding boxes.
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160
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161 - **segment** – Use this if your pre-trained/trained model is a segmentation model. It outputs text file containing polygons coordinates, class IDs and confidence score and overlaid images with bounding boxes and mask images.
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162
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163 ⚠️ **Important:** The selected mode must match the type of the model you upload. For example, if you are using a segmentation model (`*-seg.pt`), you must select `segment` mode. Using a mismatched mode and model will lead to errors or empty results.
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164
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165 ---
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166
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167 **Inputs**
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168
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169 - **Input Images** (`jpg`, `png`): One or more images to analyze.
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170 - **YOLO Class Name File** (`.txt`): A plain text file listing all class names used during training (one per line).
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171 - **Model File** (`.pt`): A YOLOv8-compatible pre-trained model file.
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172 - **Prediction Mode** (`detect` or `segment`): Choose based on the model type as described above.
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173 - **Image Size** (default: `1000`): Input images will be resized to square dimensions. Larger sizes yield better accuracy but require more memory.
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174 - **Confidence Threshold** (default: `0.5`): Minimum confidence to include a detection.
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175 - **IoU Threshold** (default: `0.7`): Intersection-over-Union threshold for non-maximum suppression.
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176 - **Max Detections** (default: `300`): Maximum number of objects detected per image.
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177
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178 ---
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179
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180 **Outputs**
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181
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182 - **YOLO Annotations (.txt)**:
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183 - One file per input image.
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184 - Contains bounding boxes/polygons coordinates,predicted class ID, confidence scores.
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186 - **Segmentation Masks (.tiff)** (for `segment` mode only):
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187 - Binary images showing detected object areas.
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189 - **Images with annotations(.jpg)**:
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190 - Overlaid images with bounding boxes and/or segmentation overlay.
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192 ]]></help>
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193 <expand macro="citations" />
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194 </tool>