Differential Revision: D90237984 fbshipit-source-id: 526fd760f303bf31be4f743bdcd77760496de0de
68 lines
2.2 KiB
Python
68 lines
2.2 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
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# pyre-unsafe
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import json
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import os
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from sam3.agent.agent_core import agent_inference
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def run_single_image_inference(
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image_path,
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text_prompt,
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llm_config,
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send_generate_request,
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call_sam_service,
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output_dir="agent_output",
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debug=False,
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):
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"""Run inference on a single image with provided prompt"""
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llm_name = llm_config["name"]
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if not os.path.exists(image_path):
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raise FileNotFoundError(f"Image file not found: {image_path}")
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# Create output directory
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os.makedirs(output_dir, exist_ok=True)
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# Generate output file names
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image_basename = os.path.splitext(os.path.basename(image_path))[0]
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prompt_for_filename = text_prompt.replace("/", "_").replace(" ", "_")
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base_filename = f"{image_basename}_{prompt_for_filename}_agent_{llm_name}"
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output_json_path = os.path.join(output_dir, f"{base_filename}_pred.json")
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output_image_path = os.path.join(output_dir, f"{base_filename}_pred.png")
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agent_history_path = os.path.join(output_dir, f"{base_filename}_history.json")
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# Check if output already exists and skip
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if os.path.exists(output_json_path):
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print(f"Output JSON {output_json_path} already exists. Skipping.")
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return
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print(f"{'-'*30} Starting SAM 3 Agent Session... {'-'*30} ")
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agent_history, final_output_dict, rendered_final_output = agent_inference(
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image_path,
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text_prompt,
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send_generate_request=send_generate_request,
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call_sam_service=call_sam_service,
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output_dir=output_dir,
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debug=debug,
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)
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print(f"{'-'*30} End of SAM 3 Agent Session... {'-'*30} ")
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final_output_dict["text_prompt"] = text_prompt
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final_output_dict["image_path"] = image_path
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# Save outputs
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json.dump(final_output_dict, open(output_json_path, "w"), indent=4)
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json.dump(agent_history, open(agent_history_path, "w"), indent=4)
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rendered_final_output.save(output_image_path)
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print(f"\n✅ Successfully processed single image!")
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print(f"Output JSON: {output_json_path}")
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print(f"Output Image: {output_image_path}")
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print(f"Agent History: {agent_history_path}")
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return output_image_path
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