Keep only three examples; ArtGallery1 first

app.py

@@ -41,44 +41,9 @@ model = GenerativeInferenceModel()
 
 # Define example images and their parameters with updated values from the research
 examples = [
-    {
-        "image": os.path.join("stimuli", "farm1.jpg"),
-        "name": "farm1",
-        "wiki": "https://en.wikipedia.org/wiki/Visual_perception",
-        "papers": [
-            "[Adversarially Robust Vision](https://github.com/MadryLab/robustness)",
-            "[Generative Inference](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
-        "method": "Prior-Guided Drift Diffusion",
-        "reverse_diff": {
-            "model": "resnet50_robust",
-            "layer": "all",
-            "initial_noise": 0.0,
-            "diffusion_noise": 0.02,
-            "step_size": 1.0,
-            "iterations": 501,
-            "epsilon": 40.0
-        },
-        "inference_normalization": "off",
-        "use_adaptive_eps": False,
-        "use_adaptive_step": False,
-        "mask_center_x": 0.0,
-        "mask_center_y": 0.0,
-        "mask_radius": 0.2,
-        "mask_sigma": 0.3,
-        "eps_max_mult": 300.0,
-        "eps_min_mult": 1.0,
-        "step_max_mult": 10.0,
-        "step_min_mult": 1.0,
-    },
     {
         "image": os.path.join("stimuli", "ArtGallery1.jpg"),
         "name": "ArtGallery1",
-        "wiki": "https://en.wikipedia.org/wiki/Visual_perception",
-        "papers": [
-            "[Adversarially Robust Vision](https://github.com/MadryLab/robustness)",
-            "[Generative Inference](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
         "method": "Prior-Guided Drift Diffusion",
         "reverse_diff": {
             "model": "resnet50_robust",
@@ -102,268 +67,55 @@ examples = [
         "step_min_mult": 1.0,
     },
     {
-        "image": os.path.join("stimuli", "urbanoffice1.jpg"),
-        "name": "UrbanOffice1",
-        "wiki": "https://en.wikipedia.org/wiki/Visual_perception",
-        "papers": [
-            "[Adversarially Robust Vision](https://github.com/MadryLab/robustness)",
-            "[Generative Inference](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
+        "image": os.path.join("stimuli", "farm1.jpg"),
+        "name": "farm1",
         "method": "Prior-Guided Drift Diffusion",
         "reverse_diff": {
             "model": "resnet50_robust",
             "layer": "all",
-            "initial_noise": 1.0,
-            "diffusion_noise": 0.002,
+            "initial_noise": 0.0,
+            "diffusion_noise": 0.02,
             "step_size": 1.0,
-            "iterations": 500,
+            "iterations": 501,
             "epsilon": 40.0
         },
         "inference_normalization": "off",
         "use_adaptive_eps": False,
-        "use_adaptive_step": True,
-        "mask_center_x": 0.5,
-        "mask_center_y": 0.0,
-        "mask_radius": 0.2,
-        "mask_sigma": 0.2,
-        "eps_max_mult": 20.0,
-        "eps_min_mult": 1.0,
-        "step_max_mult": 50.0,
-        "step_min_mult": 0.2,
-    },
-    {
-        "image": os.path.join("stimuli", "Neon_Color_Circle.jpg"),
-        "name": "Neon Color Spreading",
-        "wiki": "https://en.wikipedia.org/wiki/Neon_color_spreading",
-        "papers": [
-            "[Color Assimilation](https://doi.org/10.1016/j.visres.2000.200.1)",
-            "[Perceptual Filling-in](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
-        "method": "Prior-Guided Drift Diffusion",
-        "reverse_diff": {
-            "model": "resnet50_robust",
-            "layer": "layer3",
-            "initial_noise": 0.8,
-            "diffusion_noise": 0.003,
-            "step_size": 1.0,
-            "iterations": 101,
-            "epsilon": 20.0
-        },
-        "use_adaptive_eps": False,
         "use_adaptive_step": False,
         "mask_center_x": 0.0,
         "mask_center_y": 0.0,
         "mask_radius": 0.2,
-        "mask_sigma": 1.0,
-        "eps_max_mult": 1.0,
+        "mask_sigma": 0.3,
+        "eps_max_mult": 300.0,
         "eps_min_mult": 1.0,
-        "step_max_mult": 1.0,
+        "step_max_mult": 10.0,
         "step_min_mult": 1.0,
     },
     {
-        "image": os.path.join("stimuli", "Kanizsa_square.jpg"),
-        "name": "Kanizsa Square",
-        "wiki": "https://en.wikipedia.org/wiki/Kanizsa_triangle",
-        "papers": [
-            "[Gestalt Psychology](https://en.wikipedia.org/wiki/Gestalt_psychology)",
-            "[Neural Mechanisms](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
+        "image": os.path.join("stimuli", "urbanoffice1.jpg"),
+        "name": "UrbanOffice1",
         "method": "Prior-Guided Drift Diffusion",
         "reverse_diff": {
             "model": "resnet50_robust",
             "layer": "all",
-            "initial_noise": 0.0,
-            "diffusion_noise": 0.005,
-            "step_size": 0.64,
-            "iterations": 100,
-            "epsilon": 5.0
-        },
-        "use_adaptive_eps": False,
-        "use_adaptive_step": False,
-        "mask_center_x": 0.0,
-        "mask_center_y": 0.0,
-        "mask_radius": 0.2,
-        "mask_sigma": 1.0,
-        "eps_max_mult": 1.0,
-        "eps_min_mult": 1.0,
-        "step_max_mult": 1.0,
-        "step_min_mult": 1.0,
-    },
-    {
-        "image": os.path.join("stimuli", "CornsweetBlock.png"),
-        "name": "Cornsweet Illusion",
-        "wiki": "https://en.wikipedia.org/wiki/Cornsweet_illusion",
-        "papers": [
-            "[Brightness Perception](https://doi.org/10.1016/j.visres.2000.200.1)",
-            "[Edge Effects](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
-        "instructions": "Both blocks are gray in color (the same), use your finger to cover the middle line. Hit 'Load Parameters' and then hit 'Run Generative Inference' to see how the model sees the blocks.",
-        "method": "Prior-Guided Drift Diffusion",
-        "reverse_diff": {
-            "model": "resnet50_robust",
-            "layer": "layer3",
-            "initial_noise": 0.5,
-            "diffusion_noise": 0.005,
-            "step_size": 0.8,
-            "iterations": 51,
-            "epsilon": 20.0
-        },
-        "use_adaptive_eps": False,
-        "use_adaptive_step": False,
-        "mask_center_x": 0.0,
-        "mask_center_y": 0.0,
-        "mask_radius": 0.2,
-        "mask_sigma": 1.0,
-        "eps_max_mult": 1.0,
-        "eps_min_mult": 1.0,
-        "step_max_mult": 1.0,
-        "step_min_mult": 1.0,
-    },
-    {
-        "image": os.path.join("stimuli", "face_vase.png"),
-        "name": "Rubin's Face-Vase (Object Prior)",
-        "wiki": "https://en.wikipedia.org/wiki/Rubin_vase",
-        "papers": [
-            "[Figure-Ground Perception](https://en.wikipedia.org/wiki/Figure-ground_(perception))",
-            "[Bistable Perception](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
-        "method": "Prior-Guided Drift Diffusion",
-        "reverse_diff": {
-            "model": "resnet50_robust",
-            "layer": "avgpool",
-            "initial_noise": 0.9,
-            "diffusion_noise": 0.003,
-            "step_size": 0.58,
-            "iterations": 100,
-            "epsilon": 0.81
-        },
-        "use_adaptive_eps": False,
-        "use_adaptive_step": False,
-        "mask_center_x": 0.0,
-        "mask_center_y": 0.0,
-        "mask_radius": 0.2,
-        "mask_sigma": 1.0,
-        "eps_max_mult": 1.0,
-        "eps_min_mult": 1.0,
-        "step_max_mult": 1.0,
-        "step_min_mult": 1.0,
-    },
-    {
-        "image": os.path.join("stimuli", "Confetti_illusion.png"),
-        "name": "Confetti Illusion",
-        "wiki": "https://www.youtube.com/watch?v=SvEiEi8O7QE",
-        "papers": [
-            "[Color Perception](https://doi.org/10.1016/j.visres.2000.200.1)",
-            "[Context Effects](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
-        "method": "Prior-Guided Drift Diffusion",
-        "reverse_diff": {
-            "model": "resnet50_robust",
-            "layer": "layer3",
-            "initial_noise": 0.1,
-            "diffusion_noise": 0.003,
-            "step_size": 0.5,
-            "iterations": 101,
-            "epsilon": 20.0
-        },
-        "use_adaptive_eps": False,
-        "use_adaptive_step": False,
-        "mask_center_x": 0.0,
-        "mask_center_y": 0.0,
-        "mask_radius": 0.2,
-        "mask_sigma": 1.0,
-        "eps_max_mult": 1.0,
-        "eps_min_mult": 1.0,
-        "step_max_mult": 1.0,
-        "step_min_mult": 1.0,
-    },
-    {
-        "image": os.path.join("stimuli", "EhresteinSingleColor.png"),
-        "name": "Ehrenstein Illusion",
-        "wiki": "https://en.wikipedia.org/wiki/Ehrenstein_illusion",
-        "papers": [
-            "[Subjective Contours](https://doi.org/10.1016/j.visres.2000.200.1)",
-            "[Neural Processing](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
-        "method": "Prior-Guided Drift Diffusion",
-        "reverse_diff": {
-            "model": "resnet50_robust",
-            "layer": "layer3",
-            "initial_noise": 0.5,
-            "diffusion_noise": 0.005,
-            "step_size": 0.8,
-            "iterations": 101,
-            "epsilon": 20.0
-        },
-        "use_adaptive_eps": False,
-        "use_adaptive_step": False,
-        "mask_center_x": 0.0,
-        "mask_center_y": 0.0,
-        "mask_radius": 0.2,
-        "mask_sigma": 1.0,
-        "eps_max_mult": 1.0,
-        "eps_min_mult": 1.0,
-        "step_max_mult": 1.0,
-        "step_min_mult": 1.0,
-    },
-    {
-        "image": os.path.join("stimuli", "GroupingByContinuity.png"),
-        "name": "Grouping by Continuity",
-        "wiki": "https://en.wikipedia.org/wiki/Principles_of_grouping",
-        "papers": [
-            "[Gestalt Principles](https://en.wikipedia.org/wiki/Gestalt_psychology)",
-            "[Visual Organization](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
-        "method": "Prior-Guided Drift Diffusion",
-        "reverse_diff": {
-            "model": "resnet50_robust",
-            "layer": "layer3",
-            "initial_noise": 0.0,
-            "diffusion_noise": 0.005,
-            "step_size": 0.4,
-            "iterations": 101,
-            "epsilon": 4.0
+            "initial_noise": 1.0,
+            "diffusion_noise": 0.002,
+            "step_size": 1.0,
+            "iterations": 500,
+            "epsilon": 40.0
         },
+        "inference_normalization": "off",
         "use_adaptive_eps": False,
-        "use_adaptive_step": False,
-        "mask_center_x": 0.0,
+        "use_adaptive_step": True,
+        "mask_center_x": 0.5,
         "mask_center_y": 0.0,
         "mask_radius": 0.2,
-        "mask_sigma": 1.0,
-        "eps_max_mult": 1.0,
+        "mask_sigma": 0.2,
+        "eps_max_mult": 20.0,
         "eps_min_mult": 1.0,
-        "step_max_mult": 1.0,
-        "step_min_mult": 1.0,
+        "step_max_mult": 50.0,
+        "step_min_mult": 0.2,
     },
-    {
-        "image": os.path.join("stimuli", "figure_ground.png"),
-        "name": "Figure-Ground Illusion",
-        "wiki": "https://en.wikipedia.org/wiki/Figure-ground_(perception)",
-        "papers": [
-            "[Gestalt Principles](https://en.wikipedia.org/wiki/Gestalt_psychology)",
-            "[Perceptual Organization](https://doi.org/10.1016/j.tics.2003.08.003)"
-        ],
-        "method": "Prior-Guided Drift Diffusion",
-        "reverse_diff": {
-            "model": "resnet50_robust",
-            "layer": "layer3",
-            "initial_noise": 0.1,
-            "diffusion_noise": 0.003,
-            "step_size": 0.5,
-            "iterations": 101,
-            "epsilon": 3.0
-        },
-        "use_adaptive_eps": False,
-        "use_adaptive_step": False,
-        "mask_center_x": 0.0,
-        "mask_center_y": 0.0,
-        "mask_radius": 0.2,
-        "mask_sigma": 1.0,
-        "eps_max_mult": 1.0,
-        "eps_min_mult": 1.0,
-        "step_max_mult": 1.0,
-        "step_min_mult": 1.0,
-    }
 ]
 
 def _input_image_stem(image):
@@ -770,12 +522,6 @@ with gr.Blocks(title="Human Hallucination Prediction", css="""
             # Right column for the explanation
             with gr.Column(scale=2):
                 gr.Markdown(f"### {ex['name']}")
-                if ex["name"] not in ("farm1", "ArtGallery1", "UrbanOffice1"):
-                    gr.Markdown(f"[Read more on Wikipedia]({ex['wiki']})")
-                
-                # Show instructions if they exist
-                if "instructions" in ex:
-                    gr.Markdown(f"**Instructions:** {ex['instructions']}")
                 
         
         if i < len(examples) - 1:  # Don't add separator after the last example