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SAM3 Video Segmentation - Clean deployment
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# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import json
import os
from sam3.agent.agent_core import agent_inference
def run_single_image_inference(
image_path,
text_prompt,
llm_config,
send_generate_request,
call_sam_service,
output_dir="agent_output",
debug=False,
):
"""Run inference on a single image with provided prompt"""
llm_name = llm_config["name"]
if not os.path.exists(image_path):
raise FileNotFoundError(f"Image file not found: {image_path}")
# Create output directory
os.makedirs(output_dir, exist_ok=True)
# Generate output file names
image_basename = os.path.splitext(os.path.basename(image_path))[0]
prompt_for_filename = text_prompt.replace("/", "_").replace(" ", "_")
base_filename = f"{image_basename}_{prompt_for_filename}_agent_{llm_name}"
output_json_path = os.path.join(output_dir, f"{base_filename}_pred.json")
output_image_path = os.path.join(output_dir, f"{base_filename}_pred.png")
agent_history_path = os.path.join(output_dir, f"{base_filename}_history.json")
# Check if output already exists and skip
if os.path.exists(output_json_path):
print(f"Output JSON {output_json_path} already exists. Skipping.")
return
print(f"{'-'*30} Starting SAM 3 Agent Session... {'-'*30} ")
agent_history, final_output_dict, rendered_final_output = agent_inference(
image_path,
text_prompt,
send_generate_request=send_generate_request,
call_sam_service=call_sam_service,
output_dir=output_dir,
debug=debug,
)
print(f"{'-'*30} End of SAM 3 Agent Session... {'-'*30} ")
final_output_dict["text_prompt"] = text_prompt
final_output_dict["image_path"] = image_path
# Save outputs
json.dump(final_output_dict, open(output_json_path, "w"), indent=4)
json.dump(agent_history, open(agent_history_path, "w"), indent=4)
rendered_final_output.save(output_image_path)
print(f"\n✅ Successfully processed single image!")
print(f"Output JSON: {output_json_path}")
print(f"Output Image: {output_image_path}")
print(f"Agent History: {agent_history_path}")
return output_image_path