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import gradio as gr | |
from PIL import Image | |
from datetime import datetime | |
import pytz | |
from ocr_engine import extract_weight | |
from simple_salesforce import Salesforce | |
import base64 | |
import os | |
# Salesforce credentials (for safety, you can later store these in environment variables) | |
SF_USERNAME = "[email protected]" | |
SF_PASSWORD = "autoweight@32" | |
SF_TOKEN = "UgiHKWT0aoZRX9gvTYDjAiRY" | |
# Connect to Salesforce | |
sf = Salesforce(username=SF_USERNAME, password=SF_PASSWORD, security_token=SF_TOKEN) | |
def process_image(image): | |
if image is None: | |
return "β No image provided", "", None, gr.update(visible=True) | |
try: | |
weight = extract_weight(image) | |
ist = pytz.timezone('Asia/Kolkata') | |
timestamp = datetime.now(ist).strftime("%Y-%m-%d %H:%M:%S IST") | |
if not weight or "No valid" in weight: | |
return "β Unable to detect. Try again with a clearer image.", "", image, gr.update(visible=True) | |
# Save snapshot image to base64 (optional field, depends on usage) | |
buffered_image = image.copy() | |
buffered_image.save("snapshot.jpg") | |
with open("snapshot.jpg", "rb") as img_file: | |
snapshot_base64 = base64.b64encode(img_file.read()).decode('utf-8') | |
# Create record in Salesforce | |
sf.Weight_Log__c.create({ | |
"Captured_Weight__c": float(weight.replace("kg", "").strip()), | |
"Captured_At__c": datetime.now(ist).isoformat(), | |
"Snapshot_Image__c": snapshot_base64, | |
"Device_ID__c": "DEVICE-001", # Static or dynamic based on your design | |
"Status__c": "Captured" | |
}) | |
return weight, timestamp, image, gr.update(visible=False) | |
except Exception as e: | |
return f"Error: {str(e)}", "", None, gr.update(visible=True) | |
with gr.Blocks(css=".gr-button {background-color: #2e7d32 !important; color: white !important;}") as demo: | |
gr.Markdown(""" | |
<h1 style='text-align: center; color: #2e7d32;'>π· Auto Weight Logger</h1> | |
<p style='text-align: center;'>Upload or capture a digital weight image. Detects weight using AI OCR.</p> | |
<hr style='border: 1px solid #ddd;'/> | |
""") | |
with gr.Row(): | |
image_input = gr.Image(type="pil", label="π Upload or Capture Image") | |
detect_btn = gr.Button("π Detect Weight") | |
with gr.Row(): | |
weight_out = gr.Textbox(label="π¦ Detected Weight", placeholder="e.g., 97.9 kg", show_copy_button=True) | |
time_out = gr.Textbox(label="π Captured At (IST)", placeholder="e.g., 2025-07-01 12:00:00") | |
snapshot = gr.Image(label="πΈ Snapshot Preview") | |
retake_btn = gr.Button("π Retake / Try Again", visible=False) | |
detect_btn.click(fn=process_image, inputs=image_input, outputs=[weight_out, time_out, snapshot, retake_btn]) | |
retake_btn.click(fn=lambda: ("", "", None, gr.update(visible=False)), | |
inputs=[], outputs=[weight_out, time_out, snapshot, retake_btn]) | |
demo.launch() | |