Are the TFLite examples preventing color information from being passed along for inference?
Hi @pkgoogle,
Please look into the issue.
Thank You Hi @titanium-cranium, yes, I believe you are correct -- However the inference preprocessing should (generally) match the training preprocessing i.e. the model would have been trained on this format, For your own app, you should edit this to match your model's training format. Does this answer your question? This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you. This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further. Are you satisfied with the resolution of your issue?
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I've recently noticed in the Object Detection example, that the CameraFragment.kt code includes this line:

https://github.com/tensorflow/examples/blob/fff4bcda7201645a1efaea4534403daf5fc03d42/lite/examples/object_detection/android_play_services/app/src/main/java/org/tensorflow/lite/examples/objectdetection/fragments/CameraFragment.kt#L276

```
    private fun detectObjects(image: ImageProxy) {
        // Copy out RGB bits to the shared bitmap buffer
        image.use { bitmapBuffer.copyPixelsFromBuffer(image.planes[0].buffer) }                        <-------

        val imageRotation = image.imageInfo.rotationDegrees
        // Pass Bitmap and rotation to the object detector helper for processing and detection
        objectDetectorHelper.detect(bitmapBuffer, imageRotation)
    }
```

IIUC, then this is extracting only the grayscale out of the YUV image being passed from the camera and passing that to ObjectDetector.  Won't that destroy any sort of color based inference in the models?