gpt4

I'm doing Prolog experiments.

The grid is 1-indexed.

Top-Left Bottom-Right (TLBR) is used for object bounding boxes, like tY_lX_bY_rX where t=top l=left b=bottom r=right.

The width of the object bounding box has a 'w' prefix, like 'w5' is width=5. The height of the object bounding box has a 'h' prefix, like 'h3' is height=3.

The number of solid pixels in the object has a 'm' prefix, like 'm12' is mass=12.

The id prefixed text has no integer value and should not be considered for sorting. The number of unique IDs may be relevant. The total mass of certain IDs is sometimes preserved in the output.

% Example 1 input grid_width21_height18
object(input1_idPz7ea0g_t3_l6_b5_r8_w3_h3_m5_shapePlus_scalex1_scaley1, transform(all)).
object(input1_idPfe7a8k_t8_l7_b15_r14_w8_h8_m28_shapeBox_scaleUnknown, transform(all)).

% Example 1 output grid_width8_height8
object(output1_idPz7ea0g_t2_l2_b7_r7_w6_h6_m20_shapePlus_scalex2_scaley2, transform(all)).
object(output1_idPfe7a8k_t1_l1_b8_r8_w8_h8_m28_shapeBox_scaleUnknown, transform(all)).

% Example 2 input grid_width22_height19
object(input2_idPfe7a8k_t3_l3_b7_r7_w5_h5_m16_shapeBox_scaleUnknown, transform(all)).
object(input2_idP3d53ef_t10_l11_b12_r13_w3_h3_m5_shapeTurnedV_scaleUnknown, transform(rot90_flip270)).

% Example 2 output grid_width5_height5
object(output2_idPfe7a8k_t1_l1_b5_r5_w5_h5_m16_shapeBox_scaleUnknown, transform(all)).
object(output2_idP3d53ef_t2_l2_b4_r4_w3_h3_m5_shapeTurnedV_scaleUnknown, transform(rot90_flip270)).

% Example 3 input grid_width24_height21
object(input3_idP989a7f_t16_l14_b18_r16_w3_h3_m5_shapeLeftwardsHarpoonWithBarbUpwards_scalex1_scaley1, transform(flip270)).
object(input3_idPfe7a8k_t2_l3_b12_r13_w11_h11_m40_shapeBox_scaleUnknown, transform(all)).

% Example 3 output grid_width11_height11
object(output3_idP989a7f_t2_l2_b10_r10_w9_h9_m45_shapeLeftwardsHarpoonWithBarbUpwards_scalex3_scaley3, transform(flip270)).
object(output3_idPfe7a8k_t1_l1_b11_r11_w11_h11_m40_shapeBox_scaleUnknown, transform(all)).

There number of output objects can be different than the input objects. Also consider the rules with clockwise rotation. Check if a condition is satisfied only for objects with a certain shape. A shape can occlude another shape, so shapeL may appear as shapeRectangle. Sometimes it's the occluded object that gets transformed. Consider both euclidian distance and manhatten distance between objects. Check how much an object moves relative x, y. Check how IDs gets swapped. Don't invent new IDs. Objects that stay stationary may be a useful landmark. A landmark may be a starting point for inserting a new object next to. Check that the examples have landmarks.

Check if objects are aligned to a certain edge. Check if the mass is preserved. Count the number of object groups. Check if all the output objects agree on the same shape. Check if the shape may be a shortest path drawn between two landmarks and navigates around obstacle objects. For the objects that make it to the output, check if their shape is preserved. A line that goes from edge to edge, some condition may be satisfied above the line, but not below it. Consider where two objects are touching, maybe the touch points are different in the output, such as moving from left side to the opposite side. Consider the touch point may be at the center of another object, so objects can be moved to the center point. Check how many times an object is duplicated, does it correspond to the mass of another object or some other property. Transformations: sort, gravity towards, rotate, flipx, flipy, move, copy, merge objects, split objects, extract object, fit object inside another object, layout 2..5 objects in a direction while keeping the objects aligned and evenly spaced (remember to update tlbr coordinates). The transformation can be anything, it just have to be simple.

Task A

Think step by step, what does the examples output objects have in common. Check if they are all horizontal lines. Are they sorted in a particular way.

Task B

Think step by step, what are the transformations across all the examples, that goes from the input to the output. Write down your observations. Explain your reasoning for inserting new objects. Explain your reasoning for deleting existing objects.

Task C

Think step by step about the orientation of the output objects. Does it make sense to layout the objects in another direction. Update the object coordinates accordingly.

Task D

With the following example, I want you to predict what the output should be. Print your reasoning before the prolog code.

% Example 4 input grid_width26_height24
object(input4_idP33ffe7_t5_l21_b7_r23_w3_h3_m4_shapeCrosshair_scalex1_scaley1, transform(all)).
object(input4_idPfe7a8k_t5_l3_b18_r16_w14_h14_m52_shapeBox_scaleUnknown, transform(all)).

% Example 4 output grid_width14_height14
PREDICT the text that starts with object(output4_

Repeat the previous example prolog code, with PREDICT replaced with your predictions.

Task A

By comparing the output objects, a few patterns emerge:

The grid width and height are equivalent in the output, creating a square grid.
For each unique ID, the mass of the object remains unchanged from input to output.
The scale of each object seems to change such that it covers a more significant portion of the grid while preserving its original shape, except when the shape is occluded.
The shape of an object in the output is preserved from the input, unless it gets occluded by another object.
Most objects are moved to the top-left corner (1,1) unless there's an occluding object in the way.
It appears that objects with id 'Pfe7a8k' are stationary landmarks. They always start at (1,1) and stay there in the output. Their dimensions change to fit the square grid's size.
Other objects' TLBR values seem to be transformed in a way that they start from (2,2) and extend to fit within the grid, taking into account the landmark object if present.

Task B

Looking at transformations across examples:

First, all objects are moved to the top-left of the grid (1,1). The TLBR values are then updated to reflect this change.
The grid is resized to become a square, with dimensions equivalent to the largest dimension (width or height) in the input.
If an object with the id 'Pfe7a8k' is present, it is considered a landmark. It stays at (1,1) and resizes to cover the entire grid.
Other objects are transformed to start at (2,2) and resize to fit within the grid's remaining space, considering the landmark's new size. Their scale increases proportionally to fit the new grid.
No new objects are inserted or deleted in these transformations.

Reasoning for inserting/deleting objects: Since the transformations only involve moving, resizing, and sometimes occluding existing objects, there is no need to insert or delete any objects in these examples.

Task C

The orientation of objects in the output mainly depends on the transformations applied. However, given the flexibility of the transformations, it might make sense to layout objects in another direction depending on the context. For instance, if an object is occluded in the current orientation, it may be beneficial to move it to a different location or orientation where it can be seen more clearly.

Task D

Given the patterns and transformations identified earlier, we can predict the output for Example 4 as follows:

The grid becomes a square with dimensions 14x14.
The object with id 'Pfe7a8k' is a landmark. It stays at (1,1) but resizes to cover the entire grid (1,1,14,14).
The other object moves to start at (2,2) and resizes to fit within the remaining grid space (2,2,13,13).

Predicted output:

% Example 4 output grid_width14_height14
object(output4_idPfe7a8k_t1_l1_b14_r14_w14_h14_m52_shapeBox_scaleUnknown, transform(all)).
object(output4_idP33ffe7_t2_l2_b13_r13_w12_h12_m4_shapeCrosshair_scalex4_scaley4, transform(all)).

The scale for 'P33ffe7' has been estimated as 4 in each dimension since the object was originally 3x3 and it now fits within a 12x12 area.