Find Object - Multiple Image

This function block is designed to detect an object across multiple sections of a given main image by comparing it with a template image. It allows for precise matching even when dealing with multiple image slices.

📥 Inputs

Main Image The primary image in which you want to search for the object.

Object Image The image that contains the template of the object you want to find within the main image.

📤 Outputs

Image Any The output provides the main image with highlighting on the detected areas.

Match Count This output indicates the number of successful matches found between the main and template images.

Matched All A boolean output showing if all object templates were matched in the main image.

🕹️ Controls

Method A dropdown to select the object finding method type from a list of available template matching methods.

Match Threshold % A slider to adjust the threshold used for matching, affecting how strict the matching criteria are.

Enter Horizontal Slice Rate An input field to specify how many horizontal slices to divide the main image into during processing.

Enter Vertical Slice Rate An input field to specify how many vertical slices to divide the main image into during processing.

🎨 Features

Multi-Image Comparison Efficiently enables detection of the same object in multiple slices extracted from an image.

Flexible Template Method Selection Users can choose from various matching methods suitable for different scenarios.

Visual Feedback The output image clearly indicates matched and unmatched areas, providing immediate visual feedback.

📝 Usage Instructions

1. Input Images: Connect the main image containing the object and the template image of the object you want to detect.

2. Set Slicing Rates: Specify the number of horizontal and vertical slices for both the main image and the object template.

3. Select Matching Method: Choose the desired template matching method from the Method dropdown.

4. Set Threshold: Adjust the Match Threshold % to set the sensitivity of the matching process.

5. Run the Block: Execute the block to perform the object detection. The system will visualize the results on the output image.

📊 Evaluation

Upon executing this function block, the main image will be processed, and it will return the modified image highlighting the matched areas along with the match count and status of whether all templates were found.

💡 Tips and Tricks

Adjust Slicing Rates

Experiment with different horizontal and vertical slice rates for optimal matching performance. Too many slices might lead to unnecessary processing, while too few might miss detections.

Threshold Setting

If you have trouble finding objects, consider lowering the match threshold to increase sensitivity, allowing more matches to be considered valid.

Handling Multiple Templates

Ensure that each object template you use is clear and distinct to improve the likelihood of successful matching across different slices.

🛠️ Troubleshooting

Mismatch Warning

If you encounter a warning about mismatched slices, ensure both the main image and object image have been sliced into the same number of segments.

No Matches Found

If no matches are detected, double-check that the template image is sufficiently similar to the matching areas in the main image. You may also need to adjust the match threshold or use a different matching method.