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46 lines
2.6 KiB
Markdown
46 lines
2.6 KiB
Markdown
# Measuring Size of Objects with OpenCV
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### Calculates the size of objects based on a given reference object
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Cool object size estimator with just OpenCV and python
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All thanks to Adrian Rosebrock (from [pyimagesearch](https://www.pyimagesearch.com/)) for making
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great tutorials. This project is inspired from his blog: [Measuring size of objects in an image with OpenCV](https://www.pyimagesearch.com/2016/03/28/measuring-size-of-objects-in-an-image-with-opencv/). I have included the author's code and the one i wrote my self as well.
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## **Key Points**
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1. Steps involved:
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1. Find contours in the image.
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2. Get the minimum area rectangle for the contours.
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3. Draw the mid points and the lines joining mid points of the bounding rectangle of the contours.
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4. Grab the reference object from the contours and calculate **Pixel Per Metric** ratio.
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5. Calculate and print the bounding rectangle's dimensions based on the reference object's dimensions.
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2. Assumptions:
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1. There is a reference object in the image which is easy to find and it's width/height is know to us.
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3. Uses "Pixel Per Metric" ratio to calculate the size based on the given reference object.
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4. Reference object properties:
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1. We should know the dimensions of this object (in terms of width or height).
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2. We should be able to easily find this reference object in the image, either based on the placement of the object (like being placed in top-left corner, etc.) or via appearances (like distinctive color and/or shape).
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5. Used the United States quarter as the reference object.
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6. Used the OpenCV's find contours method to find the objects in the image and calculated their dimensions.
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## **Requirements: (with versions i tested on)**
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1. python (3.7.3)
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2. opencv (4.1.0)
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3. numpy (1.61.4)
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4. imutils (0.5.2)
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## **Commands to run the detection:**
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```
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python object_size.py --image images/example_01.png --width 0.955
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```
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## **Results:**
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The results are pretty decent even though not perfect. This is due the limitations of the image itself as its not perfect top-down view of the objects and some calibrations could have also been done in the camera before clicking the picture.
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## **The limitations**
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1. This technique requires the image to be near perfect top-down view of the objects to calculate the accurate results. Otherwise the dimensions of the objects in the image may be distorted.
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2. The photos are prone to radial and tangential lens distortion which would lead to uneven object dimensions.
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