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# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import random
import re
from collections import defaultdict
SEED = 42
random.seed(SEED)
def generate_question_and_answer(grid_dict):
"""
Generate a question + answer based on a grid dictionary.
Returns:
question (str): e.g.
"In grid 1, starting from the torus at position (row 0, column 1),
how many spheres are there to the right of it in the same row?"
answer (int): the count of target shapes in that direction.
"""
# 1. Parse all entries
positions = [] # list of (grid_id, row, col, shape)
for key, shape in grid_dict.items():
m = re.match(r"grid_(\d+)_(\d+)_(\d+)", key)
if not m:
continue
gid, r, c = map(int, m.groups())
positions.append((gid, r, c, shape))
# 2. Group by grid and compute bounds
by_grid = defaultdict(list)
for gid, r, c, shape in positions:
by_grid[gid].append((r, c, shape))
gid, cells = next(iter(by_grid.items()))
rows = [r for r, c, _ in cells]
cols = [c for r, c, _ in cells]
max_row, max_col = max(rows), max(cols)
# 3. Filter to interior cells if possible
interior = [(r, c, s) for (r, c, s) in cells
if 0 < r < max_row and 0 < c < max_col]
if interior:
ref_r, ref_c, ref_shape = random.choice(interior)
else:
# fallback for very thin grids
ref_r, ref_c, ref_shape = random.choice(cells)
# 4. Build possible directions (with predicates)
directions = []
if ref_c < max_col:
directions.append((
"to the right of it in the same row",
lambda r, c: r == ref_r and c > ref_c
))
if ref_c > 0:
directions.append((
"to the left of it in the same row",
lambda r, c: r == ref_r and c < ref_c
))
if ref_r < max_row:
directions.append((
"ahead it in the same column",
lambda r, c: c == ref_c and r > ref_r
))
if ref_r > 0:
directions.append((
"behind it in the same column",
lambda r, c: c == ref_c and r < ref_r
))
# Should always have at least one direction now
direction_text, predicate = random.choice(directions)
# 5. Pick a target shape (different from reference)
other_shapes = list({s for _, _, s in cells if s != ref_shape})
target_shape = random.choice(other_shapes)
# 6. Compute the answer
count = sum(
1
for (r, c, s) in cells
if predicate(r, c) and s == target_shape
)
# 7. Formulate the question
question = (
f"In grid {gid}, starting from the {ref_shape} at position "
f"(row {ref_r}, column {ref_c}), how many {target_shape}s are there "
f"{direction_text}?"
)
return question, count, (max_row, max_col)
import os
import json
base_dir = "3D_DoYouSeeMe/visual_spatial"
os.listdir(base_dir)
data_list = []
for filename in os.listdir(base_dir):
if filename.endswith(".json"):
# print(filename)
with open(os.path.join(base_dir, filename), "r") as f:
data = f.read()
data = json.loads(data)
q, a, (max_row, max_col) = generate_question_and_answer(data)
data_list.append({"filename": os.path.splitext(filename)[0] + ".png",
"question": q,
"answer": a,
"sweep": [max_row, max_col]})
import pandas as pd
df = pd.DataFrame(data_list)
df.to_csv(os.path.join(base_dir, "dataset_info.csv"), index=False)
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