EDN Basic version 2.0

Q: In the new version of EDN Basic I get the message “Wrong image size!”
A: In the new EDN v.2 script, the size of the image must exactly match the required height and width of the sample. For this purpose, I have created so-called template files, which can be found in the zip file or in the Downloads menu. You can see the process of cropping images in different programs in ColorBlocker videos.
Q: What does the most affect the quality of digital negatives?
A: The quality of digital negatives is mostly influenced by the poor application of light-sensitive chemicals on paper. Most often, for example, the entire left side of the paper is darker than the right side. This is seen in the raw data graph as a curve with sixteen peaks. In this case, the first solution is to dry the paper on a flat basis. Another solution is to level the base on which the image is. The third solution is to remove excess liquid with a brush. And most importantly. I usually print two samples on the same paper, turning the second upside-down. Then I calculate the average from these two (or four) samples.
Q: In the new version of EDN v.2.0, I cannot find a command to calculate the average.
A: The average is now calculated automatically. You simply drag&drop as many samples as you want to the Choose files button.
Q: Are the new Gradient maps compatible with the old Photoshop script for making the average?
A: Yes, the file format is the same, except that the results in the new version are more accurately calculated.
Q: The advantage of the EDN program would also be to use an average correction. Why?
A: Each sample we print is slightly different from the rest of the samples. Therefore, the most correct result is obtained by using as many samples as possible. We then calculate the average correction from these samples. Most often, we print four samples.
But sometimes it happens that one of the results deviates significantly from the rest of the samples. Maybe because of greasy paper, chemical contamination, poor paper coating, and the like. In this case, it is best to discard such a result as it spoils the average.
Before calculating the average result, it is, therefore, wise to review the outcome of each sample.