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<application>
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<option name="lastTrimTime" value="1768292701459" />
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<component name="Translation.OpenAISettings">
<option name="OPEN_AI">
<open-ai>
<option name="API_PATH" value="/api/paas/v4/chat/completions" />
<option name="CUSTOM_MODEL" value="glm-4-flash" />
<option name="ENDPOINT" value="https://open.bigmodel.cn" />
<option name="USE_CUSTOM_MODEL" value="true" />
</open-ai>
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<component name="Translation.Settings">
<option name="primaryLanguage" value="CHINESE_SIMPLIFIED" />
<option name="translator" value="OPEN_AI" />
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<histories>
<item value="fog" />
<item value="wireframe linejoin" />
<item value="wireframe linecap" />
<item value="wireframe linewidth" />
<item value="wireframe" />
<item value="refraction ratio" />
<item value="reflectivity" />
<item value="env map rotation" />
<item value="normal scale" />
<item value="normal map type" />
<item value="emissive" />
<item value="type" />
<item value="color" />
<item value="specular" />
<item value="shininess" />
<item value="bump scale" />
<item value="[parameters] - (optional) an object with one or more properties defining the material's appearance. Any property of the material (including any property inherited from [Material]) can be passed in here. The exception is the property [color], which can be passed in as a hexadecimal int and is 0xffffff (white) by default. [Color] is called internally." />
<item value="A material for shiny surfaces with specular highlights. The material uses a non-physically based [Blinn-Phong](https:en.wikipedia.orgwikiBlinn-Phong_shading_model) model for calculating reflectance. Unlike the Lambertian model used in the [MeshLambertMaterial] this can simulate shiny surfaces with specular highlights (such as varnished wood). [MeshPhongMaterial] uses per-fragment shading. Performance will generally be greater when using this material over the [MeshStandardMaterial] or [MeshPhysicalMaterial], at the cost of some graphical accuracy." />
<item value="flat shading" />
<item value="nav use percep" />
<item value="beverage" />
<item value="https:docs.opencv.org4.xd3d63classcv_1_1Mat.htmla51615ebf17a64c968df0bf49b4de6a3a" />
<item value="Mat (int rows, int cols, int type, void data, size_t step=AUTO_STEP)" />
<item value="This function can throw exception, so make sure to free the allocated memory inside a `try-finally` block!" />
<item value="Be careful when using this constructor, as you are responsible for managing the native pointer yourself. Improper handling may lead to memory leaks or undefined behavior." />
<item value="[data] should be raw pixels values with exactly same length of [channels] [rows] [cols]" />
<item value="Create a Mat from self-allocated buffer" />
<item value="A typed view of a sequence of bytes. It is a compile-time error for a class to attempt to extend or implement `TypedData`." />
<item value="The offset of this view into the underlying byte buffer, in bytes." />
<item value="The length of this view, in bytes." />
<item value="Releases all resources held by the detector. Call this when you're done using the detector to free up memory. After calling dispose, you must call [initialize] again before running any detections." />
<item value="aperture size" />
<item value="l 2 gradient" />
<item value="Outputs for a single detected face. [boundingBox] is the face bounding box in pixel coordinates. [landmarks] provides convenient access to 6 key facial landmarks (eyes, nose, mouth). [mesh] contains 468 facial landmarks as pixel coordinates. [eyes] contains iris center, iris contour, and eye mesh landmarks for both eyes." />
<item value="cannied" />
<item value="Canny finds edges in an image using the Canny algorithm. The function finds edges in the input image image and marks them in the output map edges using the Canny algorithm. The smallest value between threshold1 and threshold2 is used for edge linking. The largest value is used to find initial segments of strong edges." />
<item value="[data] will be copied 2 times, use [Mat.fromVec] or [Mat.fromBuffer] if better performance" />
<item value="[data] should be raw pixels values with exactly same length of channels [rows] [cols]" />
<item value="predefined type constants" />
<item value="Raw unmodified format. Unencoded bytes, in the image's existing format. For example, a grayscale image may use a single 8-bit channel for each pixel." />
<item value="Raw straight RGBA format. Unencoded bytes, in RGBA row-primary form with straight alpha, 8 bits per channel." />
<item value="Raw RGBA format. Unencoded bytes, in RGBA row-primary form with premultiplied alpha, 8 bits per channel." />
<item value="This combines [decodeImage] and [registerFrame] into a single operation that avoids transferring RGB data back to the main isolate. The image is decoded and stored in the worker, returning only the frameId and dimensions." />
<item value="Decodes and registers an image in one operation (optimized fast-path)." />
<item value="The [imageBytes] parameter should contain encoded image data (JPEG, PNG, etc.)." />
<item value="Specifies which face detection model variant to use. Different models are optimized for different use cases: - [frontCamera]: Optimized for selfiefront-facing camera (128x128 input) - [backCamera]: Optimized for rear camera with higher resolution (256x256 input) - [shortRange]: Optimized for close-up faces (128x128 input) - [full]: Full-range detection (192x192 input) - [fullSparse]: Full-range with sparse anchors (192x192 input)" />
<item value="judge motion and emoticon" />
<item value="put if absent" />
<item value="use penetrate" />
<item value="Counter" />
</histories>
<option name="languageScores">
<map>
<entry key="CHINESE_SIMPLIFIED" value="65" />
<entry key="ENGLISH" value="65" />
</map>
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