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Google Drive Batch Processor for TB-Guard-XAI
Automatically processes chest X-rays uploaded to Google Drive
Uses live Hugging Face Space endpoint for analysis
"""
import os
import io
import time
import requests
from pathlib import Path
from datetime import datetime
from google.oauth2.credentials import Credentials
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Request
from googleapiclient.discovery import build
from googleapiclient.http import MediaFileUpload, MediaIoBaseDownload
import pickle
from fpdf import FPDF
# Hugging Face Space endpoint
HF_SPACE_URL = "https://mistral-hackaton-2026-tb-guard-xai.hf.space" # Update with your actual URL
API_ENDPOINT = f"{HF_SPACE_URL}/analyze"
# Google Drive API scopes
SCOPES = ['https://www.googleapis.com/auth/drive']
# Folder names in Google Drive
INBOX_FOLDER = "TB_XRay_Inbox"
REPORTS_FOLDER = "TB_Reports"
PROCESSED_FOLDER = "TB_Processed"
class GoogleDriveBatchProcessor:
"""Batch processor for Google Drive integration using HF Space API"""
def __init__(self, hf_space_url=HF_SPACE_URL):
self.service = self.authenticate()
self.api_endpoint = f"{hf_space_url}/analyze"
self.processed_files = set()
# Test API connection
print(f"π Testing connection to Hugging Face Space...")
print(f" URL: {hf_space_url}")
try:
response = requests.get(f"{hf_space_url}/status", timeout=10)
if response.status_code == 200:
print(f" β
API is online and ready!")
else:
print(f" β οΈ API returned status {response.status_code}")
except Exception as e:
print(f" β οΈ Could not connect to API: {e}")
print(f" π‘ Make sure your Hugging Face Space is running")
# Create folders if they don't exist
self.inbox_id = self.get_or_create_folder(INBOX_FOLDER)
self.reports_id = self.get_or_create_folder(REPORTS_FOLDER)
self.processed_id = self.get_or_create_folder(PROCESSED_FOLDER)
print(f"\nβ
Google Drive folders ready:")
print(f" π₯ Inbox: {INBOX_FOLDER}")
print(f" π Reports: {REPORTS_FOLDER}")
print(f" β
Processed: {PROCESSED_FOLDER}")
def authenticate(self):
"""Authenticate with Google Drive API"""
creds = None
# Token file stores user's access and refresh tokens
if os.path.exists('token.pickle'):
with open('token.pickle', 'rb') as token:
creds = pickle.load(token)
# If no valid credentials, let user log in
if not creds or not creds.valid:
if creds and creds.expired and creds.refresh_token:
creds.refresh(Request())
else:
if not os.path.exists('credentials.json'):
print("β ERROR: credentials.json not found!")
print("\nπ Setup Instructions:")
print("1. Go to https://console.cloud.google.com/")
print("2. Create a new project or select existing")
print("3. Enable Google Drive API")
print("4. Create OAuth 2.0 credentials (Desktop app)")
print("5. Download credentials.json to this folder")
print("6. Run this script again")
raise FileNotFoundError("credentials.json not found")
flow = InstalledAppFlow.from_client_secrets_file(
'credentials.json', SCOPES)
creds = flow.run_local_server(port=0)
# Save credentials for next run
with open('token.pickle', 'wb') as token:
pickle.dump(creds, token)
return build('drive', 'v3', credentials=creds)
def get_or_create_folder(self, folder_name):
"""Get folder ID or create if doesn't exist"""
# Search for folder
query = f"name='{folder_name}' and mimeType='application/vnd.google-apps.folder' and trashed=false"
results = self.service.files().list(q=query, fields="files(id, name)").execute()
folders = results.get('files', [])
if folders:
return folders[0]['id']
# Create folder
file_metadata = {
'name': folder_name,
'mimeType': 'application/vnd.google-apps.folder'
}
folder = self.service.files().create(body=file_metadata, fields='id').execute()
print(f"π Created folder: {folder_name}")
return folder.get('id')
def list_inbox_files(self):
"""List all image files in inbox folder"""
query = f"'{self.inbox_id}' in parents and trashed=false and (mimeType='image/png' or mimeType='image/jpeg')"
results = self.service.files().list(
q=query,
fields="files(id, name, createdTime)"
).execute()
return results.get('files', [])
def download_file(self, file_id, file_name):
"""Download file from Google Drive"""
request = self.service.files().get_media(fileId=file_id)
temp_path = Path("temp_gdrive") / file_name
temp_path.parent.mkdir(exist_ok=True)
fh = io.FileIO(str(temp_path), 'wb')
downloader = MediaIoBaseDownload(fh, request)
done = False
while not done:
status, done = downloader.next_chunk()
fh.close()
return temp_path
def upload_file(self, file_path, folder_id, file_name=None):
"""Upload file to Google Drive"""
if file_name is None:
file_name = Path(file_path).name
file_metadata = {
'name': file_name,
'parents': [folder_id]
}
media = MediaFileUpload(str(file_path), resumable=True)
file = self.service.files().create(
body=file_metadata,
media_body=media,
fields='id'
).execute()
return file.get('id')
def move_file(self, file_id, new_folder_id):
"""Move file to different folder"""
# Get current parents
file = self.service.files().get(fileId=file_id, fields='parents').execute()
previous_parents = ",".join(file.get('parents'))
# Move file
self.service.files().update(
fileId=file_id,
addParents=new_folder_id,
removeParents=previous_parents,
fields='id, parents'
).execute()
def generate_pdf_report(self, file_name, analysis_result, output_path):
"""Generate PDF report from analysis results"""
pdf = FPDF()
pdf.add_page()
# Title
pdf.set_font('Arial', 'B', 16)
pdf.cell(0, 10, 'TB-Guard-XAI Clinical Report', 0, 1, 'C')
pdf.ln(5)
# Patient info
pdf.set_font('Arial', '', 10)
pdf.cell(0, 6, f'X-Ray File: {file_name}', 0, 1)
pdf.cell(0, 6, f'Analysis Date: {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}', 0, 1)
pdf.cell(0, 6, f'System: TB-Guard-XAI v2.0 (Offline Mode: {analysis_result.get("mode", "unknown")})', 0, 1)
pdf.ln(5)
# Results
pdf.set_font('Arial', 'B', 12)
pdf.cell(0, 8, 'Analysis Results:', 0, 1)
pdf.set_font('Arial', '', 10)
pdf.cell(0, 6, f'Prediction: {analysis_result["prediction"]}', 0, 1)
pdf.cell(0, 6, f'TB Probability: {analysis_result["probability"]*100:.1f}%', 0, 1)
pdf.cell(0, 6, f'Uncertainty: {analysis_result["uncertainty"]} (std: {analysis_result["uncertainty_std"]:.4f})', 0, 1)
pdf.cell(0, 6, f'Attention Region: {analysis_result.get("gradcam_region", "N/A")}', 0, 1)
pdf.ln(5)
# Clinical synthesis
pdf.set_font('Arial', 'B', 12)
pdf.cell(0, 8, 'Clinical Synthesis:', 0, 1)
pdf.set_font('Arial', '', 9)
synthesis = analysis_result.get("explanation", "No synthesis available")
# Clean markdown and format for PDF
synthesis = synthesis.replace('#', '').replace('*', '').replace('`', '')
# Split into lines and add to PDF
for line in synthesis.split('\n'):
line = line.strip()
if line:
pdf.multi_cell(0, 5, line)
pdf.ln(5)
# Disclaimer
pdf.set_font('Arial', 'I', 8)
pdf.multi_cell(0, 4, 'DISCLAIMER: This is a screening tool, not a diagnostic tool. All findings must be confirmed by qualified healthcare professionals and appropriate diagnostic tests.')
# Save PDF
pdf.output(str(output_path))
def analyze_xray_via_api(self, image_path):
"""Analyze X-ray using Hugging Face Space API"""
try:
# Prepare file for upload
with open(image_path, 'rb') as f:
files = {'file': (Path(image_path).name, f, 'image/png')}
data = {
'symptoms': '', # No symptoms for batch processing
'age_group': 'Adult (18-64)', # Default
'threshold': 0.5
}
# Call API
response = requests.post(
self.api_endpoint,
files=files,
data=data,
timeout=60 # 60 second timeout
)
if response.status_code == 200:
return response.json()
else:
print(f" β οΈ API error: {response.status_code}")
print(f" Response: {response.text[:200]}")
return None
except requests.exceptions.Timeout:
print(f" β οΈ API timeout (>60s)")
return None
except Exception as e:
print(f" β οΈ API call failed: {e}")
return None
def process_file(self, file_info):
"""Process a single X-ray file using HF Space API"""
file_id = file_info['id']
file_name = file_info['name']
print(f"\nπ Processing: {file_name}")
try:
# Download file
print(" π₯ Downloading from Google Drive...")
local_path = self.download_file(file_id, file_name)
# Analyze via API
print(" π§ Sending to Hugging Face Space for analysis...")
result = self.analyze_xray_via_api(local_path)
if result is None:
print(f" β Analysis failed for {file_name}")
local_path.unlink()
return False
# Check for errors
if 'error' in result:
print(f" β API error: {result['error']}")
local_path.unlink()
return False
# Show results
mode = result.get('mode', 'unknown')
prob = result.get('probability', 0)
uncertainty = result.get('uncertainty', 'Unknown')
print(f" π Results: {result.get('prediction', 'Unknown')}")
print(f" β’ Probability: {prob*100:.1f}%")
print(f" β’ Uncertainty: {uncertainty}")
print(f" β’ Mode: {mode.upper()}")
# Generate PDF report
print(" π Generating PDF report...")
report_name = Path(file_name).stem + "_report.pdf"
report_path = Path("temp_gdrive") / report_name
self.generate_pdf_report(file_name, result, report_path)
# Upload report
print(" π€ Uploading report to Google Drive...")
self.upload_file(report_path, self.reports_id, report_name)
# Move original to processed folder
print(" β
Moving to processed folder...")
self.move_file(file_id, self.processed_id)
# Cleanup
local_path.unlink()
report_path.unlink()
print(f" β
Complete: {file_name} β {report_name}")
return True
except Exception as e:
print(f" β Error processing {file_name}: {e}")
import traceback
traceback.print_exc()
return False
def watch_and_process(self, interval=30):
"""Watch inbox folder and process new files"""
print("\n" + "="*60)
print("π TB-Guard-XAI Google Drive Batch Processor")
print("="*60)
print(f"\nπ Watching folder: {INBOX_FOLDER}")
print(f"β±οΈ Check interval: {interval} seconds")
print(f"π Reports will be saved to: {REPORTS_FOLDER}")
print("\nπ‘ Upload X-ray images to '{INBOX_FOLDER}' folder in Google Drive")
print("π Press Ctrl+C to stop\n")
try:
while True:
# List files in inbox
files = self.list_inbox_files()
# Filter out already processed
new_files = [f for f in files if f['id'] not in self.processed_files]
if new_files:
print(f"\n㪠Found {len(new_files)} new file(s)")
for file_info in new_files:
success = self.process_file(file_info)
if success:
self.processed_files.add(file_info['id'])
else:
print(f"β³ {datetime.now().strftime('%H:%M:%S')} - No new files. Waiting...")
time.sleep(interval)
except KeyboardInterrupt:
print("\n\nπ Stopping batch processor...")
print("β
Processed files will remain in Google Drive")
def main():
"""Main entry point"""
import sys
print("π§ Initializing TB-Guard-XAI Batch Processor...")
print("π Using Hugging Face Space API for analysis")
# Allow custom HF Space URL
hf_url = os.getenv("HF_SPACE_URL", HF_SPACE_URL)
if len(sys.argv) > 1 and sys.argv[1].startswith("http"):
hf_url = sys.argv[1]
print(f"π Using custom URL: {hf_url}")
try:
processor = GoogleDriveBatchProcessor(hf_space_url=hf_url)
# Check for command line arguments
if len(sys.argv) > 1 and sys.argv[-1] == "once":
# Process once and exit
files = processor.list_inbox_files()
if files:
print(f"\n㪠Found {len(files)} file(s) to process")
for file_info in files:
processor.process_file(file_info)
else:
print("\nπ No files in inbox")
else:
# Watch mode (default)
processor.watch_and_process(interval=30)
except FileNotFoundError as e:
print(f"\nβ {e}")
except Exception as e:
print(f"\nβ Error: {e}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
main()
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