Add hardware info

benchmark/multi_reference/deepremaster/index.md

@@ -3,11 +3,13 @@ title: 'Deepremaster: Multi reference'
 layout: default
 tag: deepremaster
 category: multi_reference
-last_modified_at: '2024-03-19 16:00:27.259599'
+last_modified_at: '2024-03-19 17:12:03.379290'
 ---
 # Multi reference
 ## Deepremaster
 
+Paper: [https://github.com/satoshiiizuka/siggraphasia2019_remastering]()
+
 This model is originally designed for film colorization.
 To run this benchmark the input image is duplicated 5 times.
 The reference images are supposed to be colored frames chosen from the movies.
@@ -33,11 +35,12 @@ See noise test vs gray test.
 
 ### Additional Information
 
-- Last updated: {{ "2024-03-19 16:01:17" | date: site.minima.date_format }}
-- Paper: [https://github.com/satoshiiizuka/siggraphasia2019_remastering]()
-
+- Last updated: {{ "2024-03-19 17:12:03" | date: site.minima.date_format }}
+- GPU info: NVIDIA GeForce GTX 1080 Ti 11 GB, Compute Capability 6.1
+- CUDA version: 11.8
+- PyTorch version: 2.2.1
 
-### Other categories:
+### Other Categories:
 
 {% for p in site.pages %}
 {% if p.tag == "deepremaster" and p.url != page.url %}

benchmark/single_reference/deepremaster/index.md

@@ -3,11 +3,13 @@ title: 'Deepremaster: Single reference'
 layout: default
 tag: deepremaster
 category: single_reference
-last_modified_at: '2024-03-19 15:58:21.484082'
+last_modified_at: '2024-03-19 17:12:03.363970'
 ---
 # Single reference
 ## Deepremaster
 
+Paper: [https://github.com/satoshiiizuka/siggraphasia2019_remastering]()
+
 This model is originally designed for film colorization.
 To run this benchmark the input image is duplicated 5 times.
 The reference images are supposed to be colored frames chosen from the movies.
@@ -37,11 +39,12 @@ This means that significant differences in the reference images cannot be used,
 
 ### Additional Information
 
-- Last updated: {{ "2024-03-19 16:00:27" | date: site.minima.date_format }}
-- Paper: [https://github.com/satoshiiizuka/siggraphasia2019_remastering]()
-
+- Last updated: {{ "2024-03-19 17:12:03" | date: site.minima.date_format }}
+- GPU info: NVIDIA GeForce GTX 1080 Ti 11 GB, Compute Capability 6.1
+- CUDA version: 11.8
+- PyTorch version: 2.2.1
 
-### Other categories:
+### Other Categories:
 
 {% for p in site.pages %}
 {% if p.tag == "deepremaster" and p.url != page.url %}

benchmark/single_reference/pdnla_net/index.md

@@ -3,11 +3,13 @@ title: 'Pdnla net: Single reference'
 layout: default
 tag: pdnla_net
 category: single_reference
-last_modified_at: '2024-03-19 16:01:18.739274'
+last_modified_at: '2024-03-19 17:13:35.576584'
 ---
 # Single reference
 ## Pdnla net
 
+Paper: [https://ieeexplore.ieee.org/abstract/document/10183846]()
+
 
 
 |  Task | Image #1 | Image #2 | Image #3 | Reference |
@@ -31,11 +33,12 @@ last_modified_at: '2024-03-19 16:01:18.739274'
 
 ### Additional Information
 
-- Last updated: {{ "2024-03-19 16:04:12" | date: site.minima.date_format }}
-- Paper: [https://ieeexplore.ieee.org/abstract/document/10183846]()
-
+- Last updated: {{ "2024-03-19 17:13:35" | date: site.minima.date_format }}
+- GPU info: NVIDIA GeForce GTX 1080 Ti 11 GB, Compute Capability 6.1
+- CUDA version: 11.8
+- PyTorch version: 2.2.1
 
-### Other categories:
+### Other Categories:
 
 {% for p in site.pages %}
 {% if p.tag == "pdnla_net" and p.url != page.url %}

benchmark/single_reference/transformer_for_image_colorization/index.md

@@ -0,0 +1,47 @@
+---
+title: 'Transformer for image colorization: Single reference'
+layout: default
+tag: transformer_for_image_colorization
+category: single_reference
+last_modified_at: '2024-03-19 17:13:36.104831'
+---
+# Single reference
+## Transformer for image colorization
+
+Paper: [https://dl.acm.org/doi/10.1145/3474085.3475385]()
+
+
+
+|  Task | Image #1 | Image #2 | Image #3 | Reference |
+|  ----- | ----- | ----- | ----- | ----- |
+| Recolor source | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/recolor_source/0/fortepan_183722_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/recolor_source/1/fortepan_250610_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/recolor_source/2/fortepan_183723_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/recolor_source/3/fortepan_251236_color.jpg' | relative_url }}" width="200"/> |
+| Full correspondence | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/full_correspondence/0/fortepan_201867_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/full_correspondence/1/fortepan_229825_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/full_correspondence/2/fortepan_102400_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_183723.jpg' | relative_url }}" width="200"/> |
+| Full correspondence | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/full_correspondence/3/fortepan_201867_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/full_correspondence/4/fortepan_229825_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/full_correspondence/5/fortepan_102400_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_251236.jpg' | relative_url }}" width="200"/> |
+| Partial reference | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_reference/0/fortepan_201867_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_reference/1/fortepan_229825_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_reference/2/fortepan_102400_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_183722.jpg' | relative_url }}" width="200"/> |
+| Partial reference | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_reference/3/fortepan_201867_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_reference/4/fortepan_229825_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_reference/5/fortepan_102400_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_250610.jpg' | relative_url }}" width="200"/> |
+| Partial source | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_source/0/fortepan_18476_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_source/1/fortepan_79821_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_source/2/fortepan_67270_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_183723.jpg' | relative_url }}" width="200"/> |
+| Partial source | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_source/3/fortepan_18476_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_source/4/fortepan_79821_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/partial_source/5/fortepan_67270_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_251236.jpg' | relative_url }}" width="200"/> |
+| Semantic correspondence strong | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_strong/0/fortepan_251148_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_strong/1/fortepan_97196_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_strong/2/fortepan_97191_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_183723.jpg' | relative_url }}" width="200"/> |
+| Semantic correspondence strong | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_strong/3/fortepan_251148_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_strong/4/fortepan_97196_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_strong/5/fortepan_97191_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_251236.jpg' | relative_url }}" width="200"/> |
+| Semantic correspondence weak | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_weak/0/fortepan_148611_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_weak/1/fortepan_84203_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_weak/2/fortepan_84203_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_112161.jpg' | relative_url }}" width="200"/> |
+| Semantic correspondence weak | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_weak/3/fortepan_148611_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_weak/4/fortepan_84203_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/semantic_correspondence_weak/5/fortepan_84203_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_115002.jpg' | relative_url }}" width="200"/> |
+| Distractors | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/distractors/0/fortepan_18098_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/distractors/1/fortepan_276876_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/distractors/2/fortepan_40115_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_251236.jpg' | relative_url }}" width="200"/> |
+| Random noise | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/random_noise/0/fortepan_18098_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/random_noise/1/fortepan_276876_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/random_noise/2/fortepan_40115_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/noise.jpg' | relative_url }}" width="200"/> |
+| Random noise | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/random_noise/3/fortepan_201867_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/random_noise/4/fortepan_229825_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/random_noise/5/fortepan_102400_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/noise.jpg' | relative_url }}" width="200"/> |
+| Gray | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/gray/0/fortepan_18098_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/gray/1/fortepan_276876_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/gray/2/fortepan_40115_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_40115.jpg' | relative_url }}" width="200"/> |
+| Gray | <img src="{{'/benchmark/single_reference/transformer_for_image_colorization/gray/3/fortepan_201867_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/gray/4/fortepan_229825_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/single_reference/transformer_for_image_colorization/gray/5/fortepan_102400_color.jpg' | relative_url }}" width="200"/> |<img src="{{'/benchmark/input/fortepan_102400.jpg' | relative_url }}" width="200"/> |
+
+### Additional Information
+
+- Last updated: {{ "2024-03-19 17:13:36" | date: site.minima.date_format }}
+- GPU info: NVIDIA GeForce GTX 1080 Ti 11 GB, Compute Capability 6.1
+- CUDA version: 11.8
+- PyTorch version: 2.2.1
+
+### Other Categories:
+
+{% for p in site.pages %}
+{% if p.tag == "transformer_for_image_colorization" and p.url != page.url %}
+- [{{ p.title }}]({{ p.url | relative_url }})
+{% endif %}
+{% endfor %}

benchmark/single_reference/unicolor/index.md

@@ -3,11 +3,13 @@ title: 'Unicolor: Single reference'
 layout: default
 tag: unicolor
 category: single_reference
-last_modified_at: '2024-03-19 16:04:20.252565'
+last_modified_at: '2024-03-19 17:12:11.990460'
 ---
 # Single reference
 ## Unicolor
 
+Paper: [https://arxiv.org/abs/2209.11223]()
+
 This model generates diverse results where the color is not constrained by the reference image.
 
 
@@ -32,11 +34,12 @@ This model generates diverse results where the color is not constrained by the r
 
 ### Additional Information
 
-- Last updated: {{ "2024-03-19 16:26:06" | date: site.minima.date_format }}
-- Paper: [https://arxiv.org/abs/2209.11223]()
-
+- Last updated: {{ "2024-03-19 17:12:12" | date: site.minima.date_format }}
+- GPU info: NVIDIA GeForce GTX 1080 Ti 11 GB, Compute Capability 6.1
+- CUDA version: 11.8
+- PyTorch version: 2.2.1
 
-### Other categories:
+### Other Categories:
 
 {% for p in site.pages %}
 {% if p.tag == "unicolor" and p.url != page.url %}

benchmark/unconditional/unicolor/index.md

@@ -3,12 +3,13 @@ title: 'Unicolor: Unconditional'
 layout: default
 tag: unicolor
 category: unconditional
-date: '2024-03-19 15:41:57.893350'
-last_modified_at: '2024-03-19 15:41:57.893356'
+last_modified_at: '2024-03-19 17:12:12.002132'
 ---
 # Unconditional
 ## Unicolor
 
+Paper: [https://arxiv.org/abs/2209.11223]()
+
 This model generates diverse results where the color is not constrained by the reference image.
 
 
@@ -36,11 +37,12 @@ This model generates diverse results where the color is not constrained by the r
 
 ### Additional Information
 
-- Last updated: {{ "2024-03-19 15:41:57" | date: site.minima.date_format }}
-- Paper: [https://arxiv.org/abs/2209.11223]()
-
+- Last updated: {{ "2024-03-19 17:12:12" | date: site.minima.date_format }}
+- GPU info: NVIDIA GeForce GTX 1080 Ti 11 GB, Compute Capability 6.1
+- CUDA version: 11.8
+- PyTorch version: 2.2.1
 
-### Other categories:
+### Other Categories:
 
 {% for p in site.pages %}
 {% if p.tag == "unicolor" and p.url != page.url %}