feat design相关模型迁移4090测试
fix
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@@ -93,9 +93,6 @@ OPENAI_MODEL_LIST = {"gpt-3.5-turbo-0613",
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"gpt-4-0613",
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"gpt-4-32k-0613", }
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# attribute service config
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ATT_TRITON_URL = "10.1.1.240:10000"
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# SR service config
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SR_MODEL_NAME = "super_resolution"
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SR_TRITON_URL = "10.1.1.240:10031"
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@@ -132,7 +129,6 @@ GRI_MODEL_NAME_SINGLE = 'stable_diffusion_1_5_relight'
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GRI_MODEL_URL = '10.1.1.240:10051'
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# SEG service config
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SEG_MODEL_URL = '10.1.1.240:10000'
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SEGMENTATION = {
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"new_model_name": "seg_knet",
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"name": "seg_ocrnet_hr18",
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@@ -141,7 +137,7 @@ SEGMENTATION = {
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}
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# DESIGN config
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DESIGN_MODEL_URL = '10.1.1.240:10000'
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DESIGN_MODEL_URL = '10.1.1.243:10000'
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AIDA_CLOTHING = "aida-clothing"
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KEYPOINT_RESULT_TABLE_FIELD_SET = ('neckline_left', 'neckline_right', 'shoulder_left', 'shoulder_right', 'armpit_left', 'armpit_right',
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'cuff_left_in', 'cuff_left_out', 'cuff_right_in', 'cuff_right_out', 'waistband_left', 'waistband_right')
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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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