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Computer vision course exercises

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Scraping details of products from ecommerce websites using python

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Models and examples built with TensorFlow

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A simple song recommender using python and GUI using Tkinter

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This repository contains recent research on fake news.

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Deep Learning Specialization by Andrew Ng on Coursera.

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MediaPipe is a cross-platform framework for building multimodal applied machine learning pipelines

https://mediapipe.dev

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issue closedgoogle/mediapipe

Mediapipe Hair Color using Slider error

I was trying to do this, as suggested in your latest comment from this issue thread https://github.com/google/mediapipe/issues/18 ,by setting flip_vertically: true in the graph , I was able to fix the invert issue.

Also about the Color Slider, It does not work but when I set the r/g/b packets to hardcode a single color when calling addConsumablePacketToInputStream(). How to fix this ?

closed time in 2 months

SwatiModi

issue commentgoogle/mediapipe

Mediapipe Hair Color using Slider error

It works, Thanks.

SwatiModi

comment created time in 2 months

issue openedgoogle/mediapipe

Mediapipe Hair Color using Slider error

created time in 2 months

issue commentgoogle/mediapipe

Is there a way to change color in real time on the hair segmentation android?

I was trying to do this, as suggested in your latest comment, by setting flip_vertically: true in the graph , I was able to fix the invert issue but the mask quality seems bad now.

Also about the Color Slider, It does not work but when I set the r/g/b packets to hardcode a single color when calling addConsumablePacketToInputStream(). How to fix this ?

sandipan1

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issue commenttensorflow/tensorflow

Support for Mediapipe tflite ops.

I was facing this issue but got a solution,

The initial code for Opresolver was

tflite::ops::builtin::BuiltinOpResolver resolver;

replace it by

builtins.AddCustom("MaxPoolingWithArgmax2D", RegisterMaxPoolingWithArgmax2D());
builtins.AddCustom("MaxUnpooling2D", RegisterMaxUnpooling2D());
builtins.AddCustom("Convolution2DTransposeBias", RegisterConvolution2DTransposeBias());
std::unique_ptr<tflite::Interpreter> interpreter;
tflite::InterpreterBuilder(*model.get(), builtins)(&interpreter);

Also add the following code of the Custom Layers from the file <a href = "https://github.com/google/mediapipe/blob/master/mediapipe/util/tflite/op_resolver.cc">here</a>

TfLiteRegistration* RegisterMaxPoolingWithArgmax2D() {
  static TfLiteRegistration reg = {
      [](TfLiteContext*, const char*, size_t) -> void* {
        return new TfLitePaddingValues();
      },
      [](TfLiteContext*, void* buffer) -> void {
        delete reinterpret_cast<TfLitePaddingValues*>(buffer);
      },
      [](TfLiteContext* context, TfLiteNode* node) -> TfLiteStatus {
        return kTfLiteOk;
      },
      [](TfLiteContext* context, TfLiteNode*) -> TfLiteStatus {
        context->ReportError(
            context, "MaxPoolingWixthArgmax2D is only available on the GPU.");
        return kTfLiteError;
      },
  };
  return &reg;
}

TfLiteRegistration* RegisterMaxUnpooling2D( ) {
  static TfLiteRegistration reg = {nullptr, nullptr, nullptr, nullptr};
  return &reg;
}

TfLiteRegistration* RegisterConvolution2DTransposeBias() {
  static TfLiteRegistration reg = {nullptr, nullptr, nullptr, nullptr};
  return &reg;
}

And include the following headers

#include "mediapipe/mediapipe/util/tflite/op_resolver.h"
#include "tensorflow/lite/builtin_op_data.h"
SanthoshRajendiran

comment created time in 3 months

issue openedtensorflow/tensorflow

System information Google colab: TensorFlow 2.0.0

<em>Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template</em>

System information

  • Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
  • OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
  • Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
  • TensorFlow installed from (source or binary):
  • TensorFlow version (use command below):
  • Python version:
  • Bazel version (if compiling from source):
  • GCC/Compiler version (if compiling from source):
  • CUDA/cuDNN version:
  • GPU model and memory:

You can collect some of this information using our environment capture script You can also obtain the TensorFlow version with: 1. TF 1.0: python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)" 2. TF 2.0: python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"

Describe the current behavior

Describe the expected behavior

Code to reproduce the issue Provide a reproducible test case that is the bare minimum necessary to generate the problem.

Other info / logs Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

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