EscVM/RAMS

#issue help wanted 8 reference for mask matrix of 1s

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#11 opened on Aug 2, 2021

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help wanted

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Description

@fsalv @EscVM With reference to https://github.com/EscVM/RAMS/issues/8#issuecomment-867725589 Matrix of how many ones should I set cropped_y_mask as ?

cropped_y_mask = tf.cast([1,1,1,1,1], tf.float32)

    cropped_predictions_masked = tf.cast(
        cropped_predictions, tf.float32)*cropped_y_mask
    cropped_labels_masked = cropped_labels*cropped_y_mask

    total_pixels_masked = tf.reduce_sum(cropped_y_mask, axis=[1, 2])

I am getting error InvalidArgumentError: Invalid reduction dimension (1 for input with 1 dimension(s) [Op:Sum] D:\SuperResolution\RAMS\utils\loss.py in l1_loss(y_true, y_pred, HR_SIZE) 50 cropped_labels_masked = cropped_labels*cropped_y_mask 51 ---> 52 total_pixels_masked = tf.reduce_sum(cropped_y_mask, axis=[1, 2]) 53 54 # bias brightness

I tried all combos cropped_y_mask =[1,1,1,1,1] cropped_y_mask =[1] cropped_y_mask =[1,1]

FullError.txt Any help appreciated

Contributor guide

Research direction
Examine the shape of cropped y mask; it should be 3D (batch, height, width) not 1D. Adjust the mask creation accordingly.
Tech stack
pythontensorflow
Domain
machine learningbackend
Issue type
Bug
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Under 1 hour
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Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Mostly clear
Prerequisites
PythonTensorFlow
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
60