C book thrill: canny edge map
A canny edge map for the published plate c-book-thrill.png, 832x1216. Canny edge detection at low threshold 0.1 and high 0.3, run at the plate's own resolution so the edges land on the same pixels as the photograph they came from. Lit coverage measures 5.6% of the frame. The plate and this map are the same scene at the same size, so they can be compared pixel for pixel rather than by eye.
Specifications
- Width
- 832
- Height
- 1216
- Coverage
- 0.0559
- Standard Deviation
- 58.57
- Derivation Kind
- canny
- Source Plate
- c-book-thrill.png
- Degenerate
- false
- Alt Text
- Book cover artwork, empty rain soaked street at night under a streetlamp, moody, as a Canny edge map, white outlines on black
- Synthetic
- true
- Disclosure
- Derived from an AI-generated plate. Synthetic, not a photograph of a real scene.
- Schema Version
- 1
Testing contract
Expected to pass- Scenario
- Open this canny map and the published plate c-book-thrill.png, compare their dimensions, then measure the share of the frame that is lit.
- Expected result
- Both are 832x1216, so the map and the photograph compare pixel for pixel with no resample in between - which is the step a test should not have to trust. Lit coverage measures 5.59% of the frame.
What is a .png file?
PNG (Portable Network Graphics) is a raster image format using lossless DEFLATE compression. It supports full 8- or 16-bit-per-channel truecolor, palette, and greyscale modes with an optional alpha channel, but no animation. It is the standard choice for screenshots, logos, and graphics with sharp edges or transparency.
How to use this file
Use an example PNG to test image decoders, alpha-compositing, thumbnail generators, and format converters, or to verify that a pipeline preserves transparency and color depth on round-trip.
How to use this file for testing
“C book thrill: canny edge map” is a deterministic Novus Examples fixture for Edge detection. Canny edge maps published beside the exact image they were computed from, at the same resolution, so an edge pipeline can be compared against a known correspondence instead of judged by eye. Includes the degenerate case: a plate with no edges at all.
Documented properties for this file: 832×1216. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such, expect parsers to fail loudly rather than silently accept them.
For image AI or enhancement tools, run the model or filter on this file and diff against the clean or ground-truth companion in the same group when available. Keep seeds and documented damage parameters in your evaluation notes so regressions are attributable.
Code examples
<img src="c-book-thrill-canny.png" alt="Example image" width="640" loading="lazy">Related files
- pngA av f3: canny edge mapA canny edge map for the published plate a-av-f3.png, 1024x1024. Canny edge detection at low threshold 0.1 and high 0.3, run at the plate's own resolution so the edges land on the same pixels as the photograph they came from. Lit coverage measures 3.2% of the frame. The plate and this map are the same scene at the same size, so they can be compared pixel for pixel rather than by eye.
- pngA av f4: canny edge mapA canny edge map for the published plate a-av-f4.png, 1024x1024. Canny edge detection at low threshold 0.1 and high 0.3, run at the plate's own resolution so the edges land on the same pixels as the photograph they came from. Lit coverage measures 4.4% of the frame. The plate and this map are the same scene at the same size, so they can be compared pixel for pixel rather than by eye.
- pngA av f5: canny edge mapA canny edge map for the published plate a-av-f5.png, 1024x1024. Canny edge detection at low threshold 0.1 and high 0.3, run at the plate's own resolution so the edges land on the same pixels as the photograph they came from. Lit coverage measures 1.2% of the frame. The plate and this map are the same scene at the same size, so they can be compared pixel for pixel rather than by eye.
- pngA av m3: canny edge mapA canny edge map for the published plate a-av-m3.png, 1024x1024. Canny edge detection at low threshold 0.1 and high 0.3, run at the plate's own resolution so the edges land on the same pixels as the photograph they came from. Lit coverage measures 4.4% of the frame. The plate and this map are the same scene at the same size, so they can be compared pixel for pixel rather than by eye.
- pngA av m4: canny edge mapA canny edge map for the published plate a-av-m4.png, 1024x1024. Canny edge detection at low threshold 0.1 and high 0.3, run at the plate's own resolution so the edges land on the same pixels as the photograph they came from. Lit coverage measures 4.7% of the frame. The plate and this map are the same scene at the same size, so they can be compared pixel for pixel rather than by eye.
- pngA av m5: canny edge mapA canny edge map for the published plate a-av-m5.png, 1024x1024. Canny edge detection at low threshold 0.1 and high 0.3, run at the plate's own resolution so the edges land on the same pixels as the photograph they came from. Lit coverage measures 1.5% of the frame. The plate and this map are the same scene at the same size, so they can be compared pixel for pixel rather than by eye.
Generated by generation/comfy_derived_wave.py. Free for any use, no attribution required, license.