feat design相关模型迁移4090测试
fix
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@@ -28,7 +28,7 @@ class AttributeRecognition:
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}
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)
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self.const = const
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self.triton_client = httpclient.InferenceServerClient(url=f"{ATT_TRITON_URL}")
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self.triton_client = httpclient.InferenceServerClient(url=f"{DESIGN_MODEL_URL}")
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def get_result(self):
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for sketch in self.request_data:
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@@ -26,7 +26,7 @@ class CategoryRecognition:
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self.attr_type = pd.read_csv(CATEGORY_PATH)
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# self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
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self.request_data = []
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self.triton_client = httpclient.InferenceServerClient(url=ATT_TRITON_URL)
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self.triton_client = httpclient.InferenceServerClient(url=DESIGN_MODEL_URL)
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for sketch in request_data:
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self.request_data.append(
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{
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@@ -81,7 +81,7 @@ def get_contours(image):
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def seg_infer_image(image_obj):
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image, ori_shape = seg_preprocess(image_obj)
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client = httpclient.InferenceServerClient(url=f"{SEG_MODEL_URL}")
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client = httpclient.InferenceServerClient(url=f"{DESIGN_MODEL_URL}")
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transformed_img = image.astype(np.float32)
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# 输入集
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inputs = [
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@@ -250,7 +250,7 @@ def generate_category_recognition(image, gender):
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return preprocessed_img
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preprocessed_img = preprocess(image)
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triton_client = httpclient.InferenceServerClient(url=ATT_TRITON_URL)
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triton_client = httpclient.InferenceServerClient(url=DESIGN_MODEL_URL)
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inputs = [
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httpclient.InferInput("input__0", preprocessed_img.shape, datatype="FP32")
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