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import gradio as gr
from weight_detector import WeightDetector
import tempfile
import os
detector = WeightDetector()
def process_input(image_source: str, image_upload=None, image_url: str = "") -> dict:
"""Process webcam/image and return weight + IST time"""
temp_img_path = None
try:
# Handle webcam/image upload
if image_source == "webcam" and image_upload is not None:
img = image_upload
elif image_source == "upload" and image_upload is not None:
img = image_upload
elif image_source == "url" and image_url:
import requests
from io import BytesIO
response = requests.get(image_url)
img = Image.open(BytesIO(response.content))
else:
return {
"weight": None,
"message": "⚠️ No image provided!",
"image": None,
"time": detector.get_current_ist()
}
# Save to temp file
with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as f:
temp_img_path = f.name
img.save(f.name)
# Detect weight
return detector.detect_weight(temp_img_path)
except Exception as e:
return {
"weight": None,
"message": f"⚠️ Error: {str(e)}",
"image": None,
"time": detector.get_current_ist()
}
finally:
if temp_img_path and os.path.exists(temp_img_path):
os.remove(temp_img_path)
# Gradio UI
with gr.Blocks(title="Auto Weight Logger") as demo:
gr.Markdown("""
# **⚖️ Auto Weight Logger (7-Segment OCR)**
**Capture weight from digital balances using a webcam or image upload.**
- ✅ Optimized for **7-segment displays** (e.g., lab balances)
- 📅 Logs **IST time** automatically
- 🚫 Detects **blurry/glare** images
""")
with gr.Row():
with gr.Column():
image_source = gr.Radio(
["webcam", "upload", "url"],
label="Input Source",
value="webcam"
)
image_upload = gr.Image(
sources=["webcam", "upload"],
type="pil",
label="Capture/Upload Image",
interactive=True
)
image_url = gr.Textbox(
label="Image URL (if selected)",
visible=False
)
submit_btn = gr.Button("Detect Weight", variant="primary")
with gr.Column():
weight_value = gr.Number(
label="Detected Weight (g)",
interactive=False
)
detection_time = gr.Textbox(
label="Detection Time (IST)",
interactive=False
)
result_message = gr.Textbox(
label="Result",
interactive=False
)
annotated_image = gr.Image(
label="Annotated Image",
interactive=False
)
# Show/hide URL input
def toggle_url_visibility(source):
return gr.Textbox(visible=source == "url")
image_source.change(
toggle_url_visibility,
inputs=image_source,
outputs=image_url
)
# Process input
submit_btn.click(
process_input,
inputs=[image_source, image_upload, image_url],
outputs=[weight_value, detection_time, result_message, annotated_image]
)
demo.launch() |