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"""
Segmentation tools using SAM3.
"""
from typing import Optional, Union, List
from google.adk.tools.tool_context import ToolContext
from ..config.dependencies import get_deps_from_state
from ..config.schemas import ComponentRequest, BoundingBox
from ..services import sam
def apply_sam3_tool(
entity: str,
color: str,
morphology: str,
bboxes: List[BoundingBox],
tool_context: ToolContext
) -> dict:
"""
Segment biological components using SAM3.
Args:
entity: Object name (e.g., 'cell', 'nucleus') - use SINGULAR form
color: Color adjective (e.g., 'green', 'blue', 'pink')
morphology: Shape adjective (e.g., 'irregular', 'round')
bboxes: Bounding boxes in one of these formats:
- List of dicts: [{"ymin": 0, "xmin": 0, "ymax": 100, "xmax": 100}, ...]
- List of lists: [[ymin, xmin, ymax, xmax], ...]
Values should be 0-1000 normalized coordinates.
tool_context: Automatically injected by ADK
Returns:
dict with:
- result: Description of segmentation outcome
- mask_file: EXACT path to the .npz file containing masks
- plot_file: Path to visualization image
- count: Number of objects found
"""
deps = get_deps_from_state(tool_context.state)
# Convert bboxes to BoundingBox objects, handling multiple formats
bbox_objects = []
for b in bboxes:
if isinstance(b, dict):
# Format: {"ymin": 0, "xmin": 0, "ymax": 100, "xmax": 100}
bbox_objects.append(BoundingBox(**b))
elif isinstance(b, (list, tuple)):
# Format: [ymin, xmin, ymax, xmax] or [xmin, ymin, xmax, ymax]
if len(b) == 4:
# Assume [ymin, xmin, ymax, xmax] based on schema order
bbox_objects.append(BoundingBox(
ymin=int(b[0]),
xmin=int(b[1]),
ymax=int(b[2]),
xmax=int(b[3])
))
else:
print(f"[Warning] Skipping invalid bbox: {b}")
else:
print(f"[Warning] Skipping unrecognized bbox format: {b}")
if not bbox_objects:
return {
"result": "ERROR: No valid bounding boxes provided",
"mask_file": None,
"plot_file": None,
"count": 0,
"label": f"{color} {morphology} {entity}"
}
request = ComponentRequest(
entity=entity,
color=color,
morphology=morphology,
bboxes=bbox_objects
)
result_str = sam.execute_segmentation(deps, request)
# Generate consistent filenames
safe_label = f"{entity}".replace(" ", "_").lower()
mask_file = f"/tmp/data_{safe_label}.npz"
plot_file = f"/tmp/out_{safe_label}.png"
# Try to extract count from result
count = 0
if "Found" in result_str:
try:
count = int(result_str.split("Found")[1].split()[0])
except:
pass
return {
"result": result_str,
"mask_file": mask_file, # <-- USE THIS EXACT PATH for get_basic_stats, get_spatial_stats
"plot_file": plot_file,
"count": count,
"label": f"{color} {morphology} {entity}"
}
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