Initial commit

fbshipit-source-id: da6be2f26e3a1202f4bffde8cb980e2dcb851294

sam3/agent/inference.py

@@ -0,0 +1,65 @@
+# 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