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_width15_height15
object(input1_idP48kmo7_t5_l1_b5_r1_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input1_idP48kmo7_t1_l6_b1_r6_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input1_idPj8kdf4_t1_l7_b1_r7_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input1_idP33ffe7_t3_l15_b3_r15_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input1_idP33ffe7_t1_l8_b1_r8_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).

% Example 1 output grid_width15_height15
object(output1_idP48kmo7_t1_l1_b5_r6_w6_h5_m10_shapeL_scaleUnknown, transform(rot90_flip)).
object(output1_idPj8kdf4_t1_l7_b15_r7_w1_h15_m15_shapeRectangle_scalex1_scaley15, transform(all)).
object(output1_idP33ffe7_t1_l8_b3_r15_w8_h3_m10_shapeL_scaleUnknown, transform(rot0_flip90)).

% Example 2 input grid_width12_height12
object(input2_idPz7ea0g_t6_l12_b6_r12_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input2_idPz7ea0g_t1_l7_b1_r7_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input2_idPj8kdf4_t5_l1_b5_r1_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input2_idPj8kdf4_t1_l5_b1_r5_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input2_idP33ffe7_t9_l1_b9_r1_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input2_idP33ffe7_t1_l6_b1_r6_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).

% Example 2 output grid_width12_height12
object(output2_idPz7ea0g_t1_l7_b6_r12_w6_h6_m11_shapeL_scaleUnknown, transform(rot0_flip90)).
object(output2_idPj8kdf4_t1_l1_b5_r5_w5_h5_m9_shapeL_scaleUnknown, transform(rot90_flip)).
object(output2_idP33ffe7_t1_l1_b9_r6_w6_h9_m14_shapeL_scaleUnknown, transform(rot90_flip)).

% Example 3 input grid_width11_height11
object(input3_idP48kmo7_t10_l11_b10_r11_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input3_idP48kmo7_t1_l5_b1_r5_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input3_idP989a7f_t5_l1_b5_r1_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input3_idP989a7f_t1_l4_b1_r4_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input3_idPfe7a8k_t5_l11_b5_r11_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input3_idPfe7a8k_t1_l6_b1_r6_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).

% Example 3 output grid_width11_height11
object(output3_idP48kmo7_t1_l5_b10_r11_w7_h10_m16_shapeL_scaleUnknown, transform(rot0_flip90)).
object(output3_idP989a7f_t1_l1_b5_r4_w4_h5_m8_shapeL_scaleUnknown, transform(rot90_flip)).
object(output3_idPfe7a8k_t1_l6_b5_r11_w6_h5_m10_shapeL_scaleUnknown, transform(rot0_flip90)).

There number of output objects can be different than the input objects. Also consider the rules with clockwise rotation. 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. Transformations: sort, gravity towards, rotate, flipx, flipy, move, 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 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.

Task B

With the following example, I want you to predict what the output should be

% Example 4 input grid_width11_height11
object(input4_idPz7ea0g_t1_l5_b1_r5_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input4_idPj8kdf4_t10_l11_b10_r11_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input4_idPj8kdf4_t1_l6_b1_r6_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input4_idP989a7f_t8_l1_b8_r1_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).
object(input4_idP989a7f_t1_l4_b1_r4_w1_h1_m1_shapeRectangle_scalex1_scaley1, transform(all)).

% Example 4 output grid_width11_height11
PREDICT the text that starts with object(output4_

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

Task A

Looking at the examples, we see some recurring patterns that help us decipher the transformations that take place to convert the input to the output.

Identification of landmarks: Landmarks seem to be objects that do not move from input to output. They are used as references for the positioning of other objects.
Grouping objects with same IDs: All objects with the same ID appear to be merged into a single object in the output. The new merged object's shape can differ from the original shapes, and it might not preserve all the pixels of the original objects due to overlapping.
Positioning of objects: The output objects seem to be positioned next to landmarks or at some fixed distance from them. This could be according to the Euclidean or Manhattan distance, depending on the specific transformation.
Rotation and flipping: The output objects may undergo rotation (either 90 or 180 degrees) and/or flipping (along X or Y axis). This changes the orientation of the object, and it can be seen in the transformation attribute of the object.
Mass preservation: It is not always guaranteed that the total mass of an object is preserved after transformation. Merging can result in overlapping pixels that decrease the total mass.
Bounding box update: After the transformation, the bounding box of each object (given by top-left and bottom-right coordinates) is updated according to its new position and shape.

Task B

Given the transformations identified in Task A, let's try to predict the output for the Example 4:

% Example 4 output grid_width11_height11
object(output4_idPz7ea0g_t1_l5_b11_r5_w1_h11_m11_shapeRectangle_scalex1_scaley11, transform(all)).
object(output4_idPj8kdf4_t1_l6_b10_r11_w6_h10_m19_shapeL_scaleUnknown, transform(rot0_flip90)).
object(output4_idP989a7f_t1_l1_b8_r4_w4_h8_m12_shapeL_scaleUnknown, transform(rot90_flip)).

Explanation: Here's the reasoning behind the output:

We chose the object with id Pz7ea0g as the landmark. It remains stationary with increased height to cover the full grid height.
Objects with the same id Pj8kdf4 are merged into an L-shaped object that is positioned to the right of the landmark. It undergoes a 90 degree clockwise rotation and a flip along Y-axis (transform = rot0_flip90).
Objects with id P989a7f are merged into another L-shaped object that is positioned to the left of the landmark. It undergoes a 90 degree counter-clockwise rotation and a flip along X-axis (transform = rot90_flip).