Commit
Β·
e09eeb5
1
Parent(s):
1ba23a3
Add challenge evaluation support by patching submission file and processing predictions
Browse files
medvqa/competitions/gi-2025/task_2.py
CHANGED
@@ -1,5 +1,5 @@
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from gradio_client import Client, handle_file
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-
from huggingface_hub import snapshot_download, login, whoami
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import argparse
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import os
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import subprocess as sp
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@@ -8,6 +8,7 @@ from datetime import datetime, timezone
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import shutil # Add this import
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import json
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from huggingface_hub import HfApi, grant_access
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HF_GATE_ACESSLIST = ["SushantGautam",
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"stevenah", "vlbthambawita"]
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@@ -69,6 +70,50 @@ if os.path.isfile(os.path.join(snap_dir, "requirements.txt")):
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sp.run(["python", "-m", "pip", "install", "-q", "-r",
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f"{snap_dir}/requirements.txt"], cwd=snap_dir, check=True)
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print("π Starting your script and loading submission details...")
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sp.run(["python", f"{snap_dir}/{submission_file}"],
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cwd=snap_dir, check=True)
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@@ -115,3 +160,25 @@ else:
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print(result)
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print("Visit this URL to see the entry: π")
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Client("SimulaMet/medvqa")
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from gradio_client import Client, handle_file
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from huggingface_hub import snapshot_download, login, whoami, hf_hub_download
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import argparse
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import os
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import subprocess as sp
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import shutil # Add this import
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import json
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from huggingface_hub import HfApi, grant_access
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import re
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HF_GATE_ACESSLIST = ["SushantGautam",
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"stevenah", "vlbthambawita"]
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sp.run(["python", "-m", "pip", "install", "-q", "-r",
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f"{snap_dir}/requirements.txt"], cwd=snap_dir, check=True)
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if os.environ.get("_MEDVQA_CHALLENGE_EVALUATE_FLAG_", "FALSE") == "TRUE":
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# Patch submission file for challenge evaluation
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challenge_file = submission_file.replace(".py", "_challenge.py")
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submission_path = os.path.join(snap_dir, submission_file)
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challenge_path = os.path.join(snap_dir, challenge_file)
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with open(submission_path, "r", encoding="utf-8") as f:
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code = f.read()
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# Replace only the dataset string
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if "SimulaMet/Kvasir-VQA-test" in code:
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code = code.replace("SimulaMet/Kvasir-VQA-test",
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"SimulaMet/Kvasir-VQA-private")
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# Comment out specific lines
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lines = code.splitlines()
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for i, line in enumerate(lines):
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if ("huggingface.co/datasets" in line or
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re.search(r'^\s*prompt_to_real\s*=', line) or
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re.search(r'^\s*jsons__\s*=', line)):
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if not line.lstrip().startswith("#"):
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leading_ws = len(line) - len(line.lstrip())
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lines[i] = line[:leading_ws] + "# " + line[leading_ws:]
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# Insert new code block after 'import requests'
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for i, line in enumerate(lines):
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if "import requests" in line:
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insert_idx = i + 1
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break
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else:
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insert_idx = None
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new_block = [
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'prompt_to_real = json.load(open(hf_hub_download("SimulaMet/Kvasir-VQA-private", "real_mapping", repo_type="dataset")))',
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'jsons__ = json.load(open(hf_hub_download("SimulaMet/Kvasir-VQA-private", "imagen-test", repo_type="dataset")))',
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]
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if insert_idx is not None:
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lines[insert_idx:insert_idx] = new_block
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code = "\n".join(lines)
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with open(challenge_path, "w", encoding="utf-8") as f:
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f.write(code)
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submission_file = challenge_file
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print(f"π Challenge file created at: {challenge_path}")
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else:
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print(
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"β οΈ Challenge patch not applied: expected string not found in submission file.")
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os.exit(
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"Please check the submission file for compatibility with challenge evaluation.")
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print("π Starting your script and loading submission details...")
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sp.run(["python", f"{snap_dir}/{submission_file}"],
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cwd=snap_dir, check=True)
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print(result)
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print("Visit this URL to see the entry: π")
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Client("SimulaMet/medvqa")
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if os.environ.get("_MEDVQA_CHALLENGE_EVALUATE_FLAG_", "FALSE") == "TRUE":
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src_json = os.path.join(snap_dir, "predictions_2.json")
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if os.path.isfile(src_json):
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with open(src_json, "r", encoding="utf-8") as f:
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data = json.load(f)
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# Remove 'debug' key if present
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data.pop("debug", None)
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# Rename 'public_scores' to 'challenge_scores' if present
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if "public_scores" in data:
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data["challenge_scores"] = data.pop("public_scores")
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# Get Team_Name from submission_info
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team_name = data.get("submission_info", {}).get(
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"Team_Name", "unknown_team")
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team_name_safe = re.sub(r'[^a-zA-Z0-9_\-]', '_', team_name)
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out_json = os.path.join(os.getcwd(), f"task2_{team_name_safe}.json")
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with open(out_json, "w", encoding="utf-8") as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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print(f"β
Copied and processed predictions to: {out_json}")
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else:
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print("β predictions_1.json not found in snapshot directory!")
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# === End: Post-processing predictions_1.json ===
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