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Update README.md

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@@ -37,8 +37,8 @@ python
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  from pose_estimation_recognition_utils_rtmlib import RTMLifting, RTMPoseEstimator2D
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  # 1. 2D PoseEstimation eines Bilder
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- estimator = RTMPoseEstimator2D()
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- result2D = estimator.process_image_from_file(image_path="Zwergnase2.jpg")
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  # 2. Lifting Model laden
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  lifting = RTMLifting(num_keypoints=133, mode="ai")
@@ -53,9 +53,9 @@ python
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  from pose_estimation_recognition_utils_rtmlib import ModelLoader, Simple3DPoseLiftingModel
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- model=Simple3DPoseLiftingModel(num_keypoints=num_keypoints)
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- model.to(device)
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- model.eval()
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  model_loader=ModelLoader(
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  repo_id="fhswf/rtm133lifting",
@@ -63,7 +63,7 @@ model_loader=ModelLoader(
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  cache_dir=cache_dir,
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  )
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- state_dict=model_loader.load_model(device=device)
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  model.load_state_dict(state_dict)
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  📊 Evaluation & Leistung
 
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  from pose_estimation_recognition_utils_rtmlib import RTMLifting, RTMPoseEstimator2D
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  # 1. 2D PoseEstimation eines Bilder
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+ estimator = RTMPoseEstimator2D()\
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+ result2D = estimator.process_image_from_file(image_path="Testbild.jpg")
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  # 2. Lifting Model laden
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  lifting = RTMLifting(num_keypoints=133, mode="ai")
 
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  from pose_estimation_recognition_utils_rtmlib import ModelLoader, Simple3DPoseLiftingModel
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+ model=Simple3DPoseLiftingModel(num_keypoints=num_keypoints)\
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+ model.to(device)\
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+ model.eval()\
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  model_loader=ModelLoader(
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  repo_id="fhswf/rtm133lifting",
 
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  cache_dir=cache_dir,
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  )
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+ state_dict=model_loader.load_model(device=device)\
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  model.load_state_dict(state_dict)
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  📊 Evaluation & Leistung