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import gradio as gr
from weight_detector import WeightDetector
import tempfile
import os
from PIL import Image
import requests
from io import BytesIO
# Initialize detector
detector = WeightDetector()
def process_input(image_source: str, image_upload=None, image_url: str = "") -> dict:
"""Process image and return results with IST"""
temp_img_path = None
try:
# Handle different input types
if image_source == "upload" and image_upload is not None:
img = image_upload
elif image_source == "url" and image_url:
response = requests.get(image_url)
img = Image.open(BytesIO(response.content))
else:
return {
"weight": None,
"message": "No valid image provided",
"image": None,
"time": detector.get_current_ist()
}
# Save to temp file for processing
with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as f:
temp_img_path = f.name
img.save(f.name)
# Detect weight
weight, time, annotated_img = detector.detect_weight(temp_img_path)
# Format result message
if weight is not None:
message = f"✅ Detected weight: {weight:.2f}g at {time}"
else:
message = f"❌ No weight value detected at {time}"
return {
"weight": weight,
"message": message,
"image": annotated_img,
"time": time
}
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.unlink(temp_img_path)
# Custom CSS for better mobile display
css = """
#mobile-view {
display: none;
}
@media screen and (max-width: 768px) {
#desktop-view {
display: none;
}
#mobile-view {
display: block;
}
}
"""
# Gradio interface
with gr.Blocks(title="Auto Weight Logger", css=css) as demo:
gr.Markdown("""
# 🏋️ Auto Weight Logger
Capture or upload an image of a digital scale to automatically detect the weight value.
""")
with gr.Row():
with gr.Column():
image_source = gr.Radio(
["upload", "url"],
label="Image Source",
value="upload",
elem_id="source-select"
)
image_upload = gr.Image(
sources=["upload", "webcam"],
type="pil",
label="Upload Image or Use Webcam",
elem_id="image-upload"
)
image_url = gr.Textbox(
label="Image URL",
visible=False,
elem_id="image-url"
)
submit_btn = gr.Button("Detect Weight", variant="primary")
with gr.Column():
weight_value = gr.Number(
label="Detected Weight (grams)",
interactive=False,
elem_id="weight-value"
)
detection_time = gr.Textbox(
label="Detection Time (IST)",
interactive=False,
elem_id="detection-time"
)
result_message = gr.Textbox(
label="Result",
interactive=False,
elem_id="result-message"
)
annotated_image = gr.Image(
label="Annotated Image",
interactive=False,
elem_id="annotated-image"
)
# Mobile view toggle
with gr.Column(visible=False, elem_id="mobile-view"):
gr.Markdown("### Mobile Instructions")
gr.Markdown("1. Tap 'Webcam' to capture\n2. Tap 'Detect Weight'")
# Show/hide URL input based on selection
def toggle_url_visibility(source):
return gr.Textbox(visible=source == "url")
image_source.change(
toggle_url_visibility,
inputs=image_source,
outputs=image_url
)
# Process submission
submit_btn.click(
process_input,
inputs=[image_source, image_upload, image_url],
outputs={
"weight": weight_value,
"message": result_message,
"image": annotated_image,
"time": detection_time
}
)
# For Hugging Face Spaces
demo.launch() |