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RKNN: Fix broken models for Toolkit v2.3.2 (#19189)
* update models * don't set input_dtype: float for yolov9 (rknn)
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@ -894,7 +894,6 @@ model: # required
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width: 320
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height: 320
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input_tensor: nhwc
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input_dtype: float
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labelmap_path: /labelmap/coco-80.txt
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```
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@ -119,7 +119,7 @@ class Rknn(DetectionApi):
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model_props["model_type"] = model_type
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if model_matched:
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model_props["filename"] = model_path + f"-{soc}-v2.3.2-1.rknn"
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model_props["filename"] = model_path + f"-{soc}-v2.3.2-2.rknn"
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model_props["path"] = model_cache_dir + model_props["filename"]
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@ -140,26 +140,10 @@ class Rknn(DetectionApi):
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os.mkdir(model_cache_dir)
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urllib.request.urlretrieve(
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f"https://github.com/MarcA711/rknn-models/releases/download/v2.3.2/{filename}",
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f"https://github.com/MarcA711/rknn-models/releases/download/v2.3.2-2/{filename}",
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model_cache_dir + filename,
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)
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def check_config(self, config):
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if (config.model.width != 320) or (config.model.height != 320):
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raise Exception(
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"Make sure to set the model width and height to 320 in your config."
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)
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if config.model.input_pixel_format != "bgr":
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raise Exception(
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'Make sure to set the model input_pixel_format to "bgr" in your config.'
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)
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if config.model.input_tensor != "nhwc":
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raise Exception(
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'Make sure to set the model input_tensor to "nhwc" in your config.'
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)
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def post_process_yolonas(self, output: list[np.ndarray]):
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"""
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@param output: output of inference
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