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Update app.py
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app.py
CHANGED
@@ -2,141 +2,104 @@ import gradio as gr
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from weight_detector import WeightDetector
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import tempfile
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import os
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from PIL import Image
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import requests
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from io import BytesIO
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# Initialize detector
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detector = WeightDetector()
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def process_input(image_source: str, image_upload=None, image_url: str = "") -> dict:
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"""Process image and return
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temp_img_path = None
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try:
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# Handle
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if image_source == "
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img = image_upload
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elif image_source == "url" and image_url:
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response = requests.get(image_url)
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img = Image.open(BytesIO(response.content))
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else:
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return {
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"weight": None,
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"message": "No
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"image": None,
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"time": detector.get_current_ist()
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}
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-
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# Save to temp file
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with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as f:
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temp_img_path = f.name
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img.save(f.name)
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# Detect weight
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weight, time, annotated_img = detector.detect_weight(temp_img_path)
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# Format result message
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if weight is not None:
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message = f"✅ Detected weight: {weight:.2f}g at {time}"
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else:
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message = f"❌ No weight value detected at {time}"
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return {
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"weight": weight,
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"message": message,
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"image": annotated_img,
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"time": time
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}
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except Exception as e:
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return {
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"weight": None,
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"message": f"Error: {str(e)}",
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"image": None,
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"time": detector.get_current_ist()
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}
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finally:
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if temp_img_path and os.path.exists(temp_img_path):
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os.
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# Custom CSS for better mobile display
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css = """
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#mobile-view {
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display: none;
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}
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@media screen and (max-width: 768px) {
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#desktop-view {
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display: none;
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}
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#mobile-view {
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display: block;
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}
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}
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"""
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# Gradio
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with gr.Blocks(title="Auto Weight Logger"
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gr.Markdown("""
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#
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Capture
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""")
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with gr.Row():
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with gr.Column():
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image_source = gr.Radio(
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["upload", "url"],
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label="
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value="
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elem_id="source-select"
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)
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image_upload = gr.Image(
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sources=["
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type="pil",
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label="Upload Image
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)
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image_url = gr.Textbox(
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label="Image URL",
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visible=False
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elem_id="image-url"
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)
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submit_btn = gr.Button("Detect Weight", variant="primary")
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with gr.Column():
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weight_value = gr.Number(
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label="Detected Weight (
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interactive=False
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elem_id="weight-value"
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)
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detection_time = gr.Textbox(
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label="Detection Time (IST)",
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interactive=False
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elem_id="detection-time"
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)
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result_message = gr.Textbox(
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label="Result",
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interactive=False
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elem_id="result-message"
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)
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annotated_image = gr.Image(
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label="Annotated Image",
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interactive=False
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elem_id="annotated-image"
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)
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#
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with gr.Column(visible=False, elem_id="mobile-view"):
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gr.Markdown("### Mobile Instructions")
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gr.Markdown("1. Tap 'Webcam' to capture\n2. Tap 'Detect Weight'")
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# Show/hide URL input based on selection
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def toggle_url_visibility(source):
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return gr.Textbox(visible=source == "url")
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@@ -146,17 +109,11 @@ with gr.Blocks(title="Auto Weight Logger", css=css) as demo:
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outputs=image_url
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)
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# Process
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submit_btn.click(
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process_input,
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inputs=[image_source, image_upload, image_url],
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outputs=
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"weight": weight_value,
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"message": result_message,
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"image": annotated_image,
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"time": detection_time
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}
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)
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# For Hugging Face Spaces
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demo.launch()
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from weight_detector import WeightDetector
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import tempfile
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import os
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detector = WeightDetector()
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def process_input(image_source: str, image_upload=None, image_url: str = "") -> dict:
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"""Process webcam/image and return weight + IST time"""
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temp_img_path = None
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try:
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# Handle webcam/image upload
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if image_source == "webcam" and image_upload is not None:
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img = image_upload
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elif image_source == "upload" and image_upload is not None:
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img = image_upload
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elif image_source == "url" and image_url:
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import requests
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from io import BytesIO
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response = requests.get(image_url)
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img = Image.open(BytesIO(response.content))
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else:
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return {
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"weight": None,
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"message": "⚠️ No image provided!",
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"image": None,
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"time": detector.get_current_ist()
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}
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# Save to temp file
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with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as f:
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temp_img_path = f.name
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img.save(f.name)
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# Detect weight
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return detector.detect_weight(temp_img_path)
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except Exception as e:
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return {
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"weight": None,
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"message": f"⚠️ Error: {str(e)}",
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"image": None,
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"time": detector.get_current_ist()
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}
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finally:
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if temp_img_path and os.path.exists(temp_img_path):
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os.remove(temp_img_path)
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# Gradio UI
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with gr.Blocks(title="Auto Weight Logger") as demo:
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gr.Markdown("""
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# **⚖️ Auto Weight Logger (7-Segment OCR)**
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**Capture weight from digital balances using a webcam or image upload.**
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- ✅ Optimized for **7-segment displays** (e.g., lab balances)
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- 📅 Logs **IST time** automatically
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- 🚫 Detects **blurry/glare** images
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""")
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with gr.Row():
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with gr.Column():
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image_source = gr.Radio(
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["webcam", "upload", "url"],
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label="Input Source",
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value="webcam"
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)
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image_upload = gr.Image(
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sources=["webcam", "upload"],
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type="pil",
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label="Capture/Upload Image",
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interactive=True
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)
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image_url = gr.Textbox(
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label="Image URL (if selected)",
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visible=False
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)
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submit_btn = gr.Button("Detect Weight", variant="primary")
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with gr.Column():
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weight_value = gr.Number(
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label="Detected Weight (g)",
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interactive=False
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)
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detection_time = gr.Textbox(
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label="Detection Time (IST)",
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interactive=False
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)
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result_message = gr.Textbox(
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label="Result",
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interactive=False
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)
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annotated_image = gr.Image(
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label="Annotated Image",
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interactive=False
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)
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# Show/hide URL input
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def toggle_url_visibility(source):
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return gr.Textbox(visible=source == "url")
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outputs=image_url
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)
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# Process input
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submit_btn.click(
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process_input,
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inputs=[image_source, image_upload, image_url],
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outputs=[weight_value, detection_time, result_message, annotated_image]
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)
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demo.launch()
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