adding app file

app.py

@@ -0,0 +1,273 @@
+import gradio as gr
+import pandas as pd
+from PIL import Image
+import os
+
+# Define your sections and labels
+SECTION_LABELS = {
+    "Oil Pore Related Issues": [
+        "Very Large Pores (Not Red)",
+        "Whiteheads (Clogged Pores)",
+        "Blackheads (Clogged Pores)",
+        "Shinny Skin",
+        "Sebaceous Filaments (Sebum)"
+    ],
+    "Acne and Blemishes": [
+        "Pustules",
+        "Papules",
+        "Nodules",
+        "Cysts",
+        "Acne",
+        "Telangiectasia",
+        "Milia",
+        "Scars",
+        "Ice Berg Scars",
+    ],
+    "Redness and Irritation": [
+        "Redness",
+        "Irritation",
+    ],
+    "Dryness and Texture Issues": [
+        "Dryness",
+        "Fine Lines / Wrinkles",
+        "Skin Flakes"
+    ],
+    "Aging and Elasticity Issues": [
+        "Loose Skin",
+        "Deep Wrinkles"
+    ],
+    "Pigmentation Issues": [
+        "Dark Spots",
+        "Melasma",
+        "Freckles"
+    ],
+    "Rosacea": [
+        "Erythematous Telangiectasia Rosacea",
+        "Papillopustular Rosacea",
+        "Fimatoz Rosacea",
+        "Ocular Rosacea"
+    ],
+    "Eczema": [
+        "Seboreik Dermatit"
+    ]
+}
+
+# Define the sections for each column to control UI layout
+column1_sections = ["Oil Pore Related Issues", "Dryness and Texture Issues"]
+column2_sections = ["Acne and Blemishes"]
+column3_sections = ["Redness and Irritation", "Pigmentation Issues", "Aging and Elasticity Issues"]
+column4_sections = ["Rosacea", "Egzama"]
+
+# Combine all section lists to define the exact UI order
+UI_ORDERED_SECTIONS = column1_sections + column2_sections + column3_sections + column4_sections
+
+# Flattened labels list, created in the SAME order as the UI checkboxes will be. This is the fix.
+ALL_LABELS = [
+    label
+    for section_name in UI_ORDERED_SECTIONS
+    for label in SECTION_LABELS.get(section_name, [])
+]
+
+
+# Global state
+images = []
+current_index = 0
+results = []
+annotations = {}
+
+# Core functions
+
+def display_image(idx):
+    """Displays the image at the given index and its saved annotations."""
+    if images:
+        img_path = images[idx]
+        img = Image.open(img_path)
+        fname = os.path.basename(img_path)
+        tick = ' ✅' if idx in annotations else ''
+        caption = f"{fname} ({idx+1}/{len(images)}){tick}"
+        states = annotations.get(idx, [False] * len(ALL_LABELS))
+        return [img, caption] + states
+    return [None, "No images uploaded"] + [False] * len(ALL_LABELS)
+
+
+def navigate(delta):
+    """Navigates to the next or previous image."""
+    global current_index
+    if not images:
+        return [None, "No images uploaded"] + [False] * len(ALL_LABELS)
+    current_index = (current_index + delta + len(images)) % len(images)
+    return display_image(current_index)
+
+
+def submit(*selections):
+    """Saves the current annotations to the state and writes to a CSV file."""
+    if not images:
+        return "No image to label", None
+
+    # Save selections to our annotations dictionary
+    annotations[current_index] = list(selections)
+    fname = os.path.basename(images[current_index])
+    chosen_labels = [lbl for lbl, sel in zip(ALL_LABELS, selections) if sel]
+    
+    global results
+    # Remove any previous entry for this image to avoid duplicates
+    results = [r for r in results if r['image'] != fname]
+    results.append({'image': fname, 'labels': ', '.join(chosen_labels)})
+
+    # Write the updated results to a CSV file
+    df = pd.DataFrame(results)
+    df.to_csv('image_labels.csv', index=False)
+
+    return "Labels saved!", 'image_labels.csv'
+
+
+def upload_images(files):
+    """Handles image uploads, resetting the application state."""
+    global images, current_index, results, annotations
+    images = [f.name for f in files]
+    current_index = 0
+    results = []
+    annotations = {}
+    outputs = display_image(0)
+    # Hide the uploader component after a successful upload
+    return outputs + [gr.update(visible=False), gr.update(visible=True)]
+
+def load_annotations(csv_file):
+    """Loads annotations from an uploaded CSV file."""
+    global annotations, results
+    if csv_file is None or not images:
+        # If no CSV is uploaded or no images are loaded, do nothing.
+        return display_image(current_index)
+
+    try:
+        df = pd.read_csv(csv_file.name)
+        # Create a quick lookup map from filename to its index in the `images` list
+        image_map = {os.path.basename(name): i for i, name in enumerate(images)}
+        
+        # Reset existing annotations and results
+        annotations = {}
+        results = df.to_dict('records')
+
+        for _, row in df.iterrows():
+            fname = row['image']
+            # Check if the image from the CSV is in the currently uploaded images
+            if fname in image_map:
+                img_idx = image_map[fname]
+                # Handle cases where labels might be empty (NaN)
+                if pd.notna(row['labels']):
+                    saved_labels = set(l.strip() for l in row['labels'].split(','))
+                else:
+                    saved_labels = set()
+                
+                # Create the boolean state list for the checkboxes
+                states = [label in saved_labels for label in ALL_LABELS]
+                annotations[img_idx] = states
+    except Exception as e:
+        print(f"Error loading annotations: {e}")
+        # In case of error, just refresh the current view without changes
+        return display_image(current_index)
+
+    # After loading, refresh the view to show the annotations for the current image
+    return display_image(current_index)
+
+
+# --- Gradio UI Definition ---
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("## Dermatology Annotation Tool")
+    with gr.Row():
+        image_upload = gr.File(label="1. Upload Images", file_count="multiple", file_types=["image"])
+        csv_upload = gr.File(label="2. (Optional) Upload Annotations CSV", file_types=[".csv"], visible=False)
+
+    checkbox_components = []
+
+    with gr.Row(): # Main row for the four columns of labels
+        # Column 1
+        with gr.Column(scale=1, min_width=0):
+            for section_name in column1_sections:
+                if section_name in SECTION_LABELS:
+                    with gr.Group():
+                        gr.Markdown(f"### {section_name}")
+                        for lbl in SECTION_LABELS[section_name]:
+                            cb = gr.Checkbox(label=lbl)
+                            checkbox_components.append(cb)
+        
+        # Column 2
+        with gr.Column(scale=1, min_width=0):
+            for section_name in column2_sections:
+                if section_name in SECTION_LABELS:
+                    with gr.Group():
+                        gr.Markdown(f"### {section_name}")
+                        for lbl in SECTION_LABELS[section_name]:
+                            cb = gr.Checkbox(label=lbl)
+                            checkbox_components.append(cb)
+
+        # Column 3
+        with gr.Column(scale=1, min_width=0):
+            for section_name in column3_sections:
+                if section_name in SECTION_LABELS:
+                    with gr.Group():
+                        gr.Markdown(f"### {section_name}")
+                        for lbl in SECTION_LABELS[section_name]:
+                            cb = gr.Checkbox(label=lbl)
+                            checkbox_components.append(cb)
+        
+        # Column 4
+        with gr.Column(scale=1, min_width=0):
+            for section_name in column4_sections:
+                if section_name in SECTION_LABELS:
+                    with gr.Group():
+                        gr.Markdown(f"### {section_name}")
+                        for lbl in SECTION_LABELS[section_name]:
+                            cb = gr.Checkbox(label=lbl)
+                            checkbox_components.append(cb)
+
+    # Image display and controls
+    with gr.Row():
+        with gr.Column(scale=2): # Image display column
+            img = gr.Image(label="Image")
+            caption = gr.Label(value="No images uploaded")
+            with gr.Row():
+                prev_btn = gr.Button("⬅️ Previous")
+                next_btn = gr.Button("Next ➡️")
+        with gr.Column(scale=1): # Controls and download column
+            submit_btn = gr.Button("Submit Labels")
+            status = gr.Label()
+            csv_downloader = gr.File(label="Download labels CSV")
+
+    # --- Event Handling ---
+    
+    # When images are uploaded
+    image_upload.upload(
+        fn=upload_images,
+        inputs=image_upload,
+        outputs=[img, caption] + checkbox_components + [image_upload, csv_upload]
+    )
+
+    # When a CSV annotation file is uploaded
+    csv_upload.upload(
+        fn=load_annotations,
+        inputs=csv_upload,
+        outputs=[img, caption] + checkbox_components
+    )
+
+    # When previous button is clicked
+    prev_btn.click(
+        fn=lambda: navigate(-1),
+        outputs=[img, caption] + checkbox_components
+    )
+
+    # When next button is clicked
+    next_btn.click(
+        fn=lambda: navigate(1),
+        outputs=[img, caption] + checkbox_components
+    )
+
+    # When submit button is clicked
+    submit_btn.click(
+        fn=submit,
+        inputs=checkbox_components,
+        outputs=[status, csv_downloader]
+    )
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)