inference

问题 I am trying to get a TensorFlow Lite example to run on a machine with an ARM Cortex-A72 processor. Unfortunately, I wasn't able to deploy a test model due to the lack of examples on how to use the C++ API. I will try to explain what I have achieved so far. Create the tflite model I have created a simple linear regression model and converted it, which should approximate the function f(x) = 2x - 1 . I got this code snippet from some tutorial, but I am unable to find it anymore. import

问题 I am trying to get a TensorFlow Lite example to run on a machine with an ARM Cortex-A72 processor. Unfortunately, I wasn't able to deploy a test model due to the lack of examples on how to use the C++ API. I will try to explain what I have achieved so far. Create the tflite model I have created a simple linear regression model and converted it, which should approximate the function f(x) = 2x - 1 . I got this code snippet from some tutorial, but I am unable to find it anymore. import

问题 I am trying to get a TensorFlow Lite example to run on a machine with an ARM Cortex-A72 processor. Unfortunately, I wasn't able to deploy a test model due to the lack of examples on how to use the C++ API. I will try to explain what I have achieved so far. Create the tflite model I have created a simple linear regression model and converted it, which should approximate the function f(x) = 2x - 1 . I got this code snippet from some tutorial, but I am unable to find it anymore. import

问题 I'm trying to create the type of an array of objects. The first and second key of this object is required to match. For example: [{ key1: "hi", key2: "world" },{ key1: 1, key2: 2 },{ key1: true, key2: false }] This is what I've come up with but it doesn't exactly work. I have a generic type to define the object in the array. When calling it to generate the array type, an error is raised. type ArrayItem<T> = { key1: T, key2: T } // This raises an error Generic Type ArrayItem requires 1 type

问题 I have an SSD tflite detection model that I am running with Python on a desktop computer. As for now, my script below takes a single image as an input for inference and it works fine: # Load TFLite model and allocate tensors. interpreter = tf.lite.Interpreter(model_path="model.tflite") interpreter.allocate_tensors() img_resized = Image.open(file_name) input_data = np.expand_dims(img_resized, axis=0) input_data = (np.float32(input_data) - input_mean) / input_std input_details = interpreter.get

来源： https://stackoverflow.com/questions/63644109/export-inference-graph-valueerror-the-passed-save-path-is-not-a-valid-checkpo

来源： https://stackoverflow.com/questions/63644109/export-inference-graph-valueerror-the-passed-save-path-is-not-a-valid-checkpo

问题 I want to use tensorflow's optimize_for_inference.py script on a frozen Model from the model zoo: the ssd_mobilenet_v1_coco . How do i find/determine the names of the input and output name of the model? Here is a link to the graph generated by tensorboard This question might help: Given a tensor flow model graph, how to find the input node and output node names (for me it did not) 回答1: We've now added some documentation on this process, covered here: https://www.tensorflow.org/mobile/prepare

问题 I want to use tensorflow's optimize_for_inference.py script on a frozen Model from the model zoo: the ssd_mobilenet_v1_coco . How do i find/determine the names of the input and output name of the model? Here is a link to the graph generated by tensorboard This question might help: Given a tensor flow model graph, how to find the input node and output node names (for me it did not) 回答1: We've now added some documentation on this process, covered here: https://www.tensorflow.org/mobile/prepare

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 7 years ago . I would like to perform non-parametric testing for a dataframe. I have three groups A,B,C. I´d like to now the statistical significance between groups A/B, B/C and A/C. How can I do that non-parametrically? When applying Kruskal-Wallis-Test, I get the overall-inference between groups. This serves as protection