Update app.py

app.py

@@ -8,45 +8,22 @@ from io import BytesIO
 from PIL import Image
 from functools import lru_cache
 
-# Load environment variables from a .env file
 load_dotenv()
 
-# --- Secure Token Management ---
-# Get the Hugging Face token from environment variables
 VIDDEXA_TOKEN = os.getenv("HF_TOKEN")
 
-# A simple cache to store loaded model instances
 _MODEL_CACHE: Dict[str, Any] = {}
 
-# --- CSS Styles ---
-# Custom CSS for the verdict card
 CUSTOM_CSS = """
 .verdict-safe { background-color: #D5F5E3; border: 2px solid #2ECC71; color: #1D8348; }
 .verdict-sensitive { background-color: #FCF3CF; border: 2px solid #F1C40F; color: #B7950B; }
 .verdict-nsfw { background-color: #FADBD8; border: 2px solid #E74C3C; color: #B03A2E; }
 .verdict-card { padding: 20px; border-radius: 10px; text-align: center; font-size: 24px; font-weight: bold; }
-
-/* Responsive Galleries: show mobile (2 cols) on small screens, desktop (4 cols) on larger */
-#examples-gallery-mobile { display: block; }
-#examples-gallery-desktop { display: none; }
-@media (min-width: 900px) {
-  #examples-gallery-mobile { display: none; }
-  #examples-gallery-desktop { display: block; }
-}
-
-/* Ensure the Viddexa logo is readable on dark backgrounds */
-.viddexa-logo {
-  background-color: #FFFFFF; /* white background behind the SVG */
-  padding: 8px;              /* a little breathing room */
-  border-radius: 8px;        /* soften the corners */
-}
-
+.viddexa-logo { background-color: #FFFFFF; padding: 8px; border-radius: 8px; }
 footer {visibility: hidden}
 """
 
 
-# --- Helper Functions ---
-
 @lru_cache(maxsize=32)
 def _download_image_bytes(image_url: str) -> bytes:
     req = Request(image_url, headers={"User-Agent": "viddexa-gradio-demo/1.0"})
@@ -60,7 +37,6 @@ def _load_model(model_id: str) -> Any:
         return _MODEL_CACHE[model_id]
     try:
         from moderators.auto_model import AutoModerator
-        # Download the model from Hugging Face
         model = AutoModerator.from_pretrained(model_id, token=VIDDEXA_TOKEN, use_fast=True)
         _MODEL_CACHE[model_id] = model
         return model
@@ -81,7 +57,6 @@ def _get_image_input(image_path: str | None, image_url: str | None) -> Image.Ima
         except Exception as fetch_err:
             raise gr.Error(f"Could not download or open the image from the URL: {fetch_err}")
     elif image_path:
-        # Open the image from a local file
         img = Image.open(image_path)
         return img.convert("RGB")
     else:
@@ -95,19 +70,15 @@ def _format_results(results: list) -> Tuple[str, Dict[str, float], str, Dict]:
 
     classifications = results[0]["classifications"]
 
-    # Normalize to a dict[str, float]
     label_output: Dict[str, float]
     if isinstance(classifications, dict):
         label_output = {str(k): float(v) for k, v in classifications.items()}
     else:
-        # Assume list[{'label': str, 'score': float}] shape
         try:
             label_output = {str(item['label']): float(item['score']) for item in classifications}
         except Exception:
-            # Fallback to empty if unexpected
             label_output = {}
 
-    # Determine the final verdict
     scores = {label.lower(): score for label, score in label_output.items()}
     nsfw_score = scores.get("nsfw", 0.0)
 
@@ -123,7 +94,6 @@ def _format_results(results: list) -> Tuple[str, Dict[str, float], str, Dict]:
 
     verdict_html = f"<div class='verdict-card {verdict_class}'>{verdict_text}</div>"
 
-    # Prepare scores for Markdown list
     markdown_output = "### All Scores\n---\n"
     for label, score in sorted(label_output.items(), key=lambda kv: kv[1], reverse=True):
         markdown_output += f"- **{label.capitalize()}**: {score:.4f}\n"
@@ -131,42 +101,27 @@ def _format_results(results: list) -> Tuple[str, Dict[str, float], str, Dict]:
     return verdict_html, label_output, markdown_output, results[0]
 
 
-# --- Main Analysis Function ---
-
 def analyze_image(image_path: str | None, image_url: str | None, model_choice: str,
                   progress=gr.Progress(track_tqdm=True)):
     """The main inference function for the Gradio interface."""
     progress(0, desc="Initializing Analysis...")
-
-    # 1. Get Image Input
     progress(0.2, desc="Processing Image...")
     input_image = _get_image_input(image_path, image_url)
-
-    # 2. Load Model
     progress(0.5, desc=f"Loading Model: {os.path.basename(model_choice)}...")
     model = _load_model(model_choice)
-
-    # 3. Run Inference
     progress(0.8, desc="Running Inference...")
     results = model(input_image)
 
-    # Helper to make model outputs JSON-serializable and in expected shape
     json_results = [
         {"classifications": getattr(r, "classifications", r)}
         for r in results
     ]
     json_results = json.loads(json.dumps(json_results, ensure_ascii=False))
 
-    # 4. Format and Return Results
     progress(1, desc="Complete!")
     return _format_results(json_results)
 
 
-def analyze_image_from_url(image_url: str, model_choice: str, progress=gr.Progress(track_tqdm=True)):
-    """Wrapper to run examples with just URL + model."""
-    return analyze_image(None, image_url, model_choice, progress)
-
-
 def analyze_image_with_status(image_path: str | None, image_url: str | None, model_choice: str,
                               progress=gr.Progress(track_tqdm=True)):
     """Run analysis and also return a user-friendly status string."""
@@ -180,7 +135,6 @@ def analyze_image_with_status(image_path: str | None, image_url: str | None, mod
     return verdict_html, label_scores, md_scores, json_obj, status
 
 
-# Example mapping for gallery selections
 EXAMPLE_ITEMS = [
     (
         "https://assets.clevelandclinic.org/transform/LargeFeatureImage/cd71f4bd-81d4-45d8-a450-74df78e4477a/Apples-184940975-770x533-1_jpg",
@@ -215,7 +169,6 @@ def run_example_by_index(evt: gr.SelectData):
     url, model, caption = EXAMPLE_ITEMS[idx]
     verdict_html, label_scores, md_scores, json_obj = analyze_image(None, url, model)
     status = f"Last analysed example: {caption}"
-    # Also update the dropdown and URL textbox for transparency
     return (
         verdict_html,
         label_scores,
@@ -232,27 +185,26 @@ with gr.Blocks(
     css=CUSTOM_CSS,
     analytics_enabled=False,
 ) as demo:
-    # Header and Introduction
     gr.HTML("""
-    <div class=\"viddexa-header\" style=\"text-align: center; max-width: 800px; margin: 0 auto;\">
-        <img class=\"viddexa-logo\" src=\"https://aky-tech.com/images/viddexa-logo.svg\" alt=\"Viddexa logo\" style=\"max-width: 320px; width: 80%; height: auto; display: block; margin: 10px auto 6px;\" />
-        <p style=\"font-size: 1.2em; color: #888;\">
-            Official demo for <a href=\"https://github.com/viddexa/moderators\" target=\"_blank\"><code>moderators</code></a> package.
+    <div class="viddexa-header" style="text-align: center; max-width: 800px; margin: 0 auto;">
+        <img class="viddexa-logo" src="https://aky-tech.com/images/viddexa-logo.svg" alt="Viddexa logo" style="max-width: 320px; width: 80%; height: auto; display: block; margin: 10px auto 6px;" />
+        <p style="font-size: 1.2em; color: #888;">
+            Official demo for <a href="https://github.com/viddexa/moderators" target="_blank"><code>moderators</code></a> package.
             <br>
             Upload an image or provide a URL to get an instant content analysis.
         </p>
         <p>
             🔗 <b>Project Links:</b>
-            <a href=\"https://huggingface.co/viddexa/nsfw-mini\" target=\"_blank\">[Model: nsfw-mini]</a> |
-            <a href=\"https://huggingface.co/viddexa/nsfw-nano\" target=\"_blank\">[Model: nsfw-nano]</a> |
-            <a href=\"https://arxiv.org/abs/2312.16338\" target=\"_blank\">[Arxiv]</a> |
-            <a href=\"https://github.com/viddexa/moderators\" target=\"_blank\">[GitHub]</a> |
-            <a href=\"https://pypi.org/project/moderators/\" target=\"_blank\">[PyPI]</a>
+            <a href="https://huggingface.co/viddexa/nsfw-mini" target="_blank">[Model: nsfw-mini]</a> |
+            <a href="https://huggingface.co/viddexa/nsfw-nano" target="_blank">[Model: nsfw-nano]</a> |
+            <a href="https://arxiv.org/abs/2312.16338" target="_blank">[Arxiv]</a> |
+            <a href="https://github.com/viddexa/moderators" target="_blank">[GitHub]</a> |
+            <a href="https://pypi.org/project/moderators/" target="_blank">[PyPI]</a>
         </p>
         <p>
         <details style="margin-top: 10px;"> 
         <summary style="cursor: pointer; font-weight: bold;">📄 BibTeX entry for citation</summary>
-        <pre style="background-color: rgba(128, 128, 128, 0.1); border: 1px solid rgba(128, 128, 128, 0.3); padding: 15px; border-radius: 5px; text-align: left; overflow-x: auto; margin: 10px 0;"><code style="font-family: monospace;"><code>@article{akyon2023nudity,
+        <pre style="background-color: rgba(128, 128, 128, 0.1); border: 1px solid rgba(128, 128, 128, 0.3); padding: 15px; border-radius: 5px; text-align: left; overflow-x: auto; margin: 10px 0;"><code style="font-family: monospace;">@article{akyon2023nudity,
   title={State-of-the-art in nudity classification: A comparative analysis},
   author={Akyon, Fatih Cagatay and Temizel, Alptekin},
   booktitle={2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)},
@@ -265,9 +217,8 @@ with gr.Blocks(
     </div>
     """)
 
-    with gr.Row(variant="panel") as main_row:
-        # Capture both columns so we can add widgets in any order
-        with gr.Column(scale=1, min_width=350) as left_col:
+    with gr.Row(variant="panel"):
+        with gr.Column(scale=1, min_width=350):
             gr.Markdown("## ⚙️ Step 1: Configure Settings")
             model_choice = gr.Dropdown(
                 choices=["viddexa/nsfw-detection-mini", "viddexa/nsfw-detection-nano"],
@@ -277,10 +228,10 @@ with gr.Blocks(
             )
 
             gr.Markdown("## 🖼️ Step 2: Provide an Image")
-            with gr.Tabs() as input_tabs:
-                with gr.TabItem("Upload Image", id="upload_tab"):
+            with gr.Tabs():
+                with gr.TabItem("Upload Image"):
                     image_input = gr.Image(type="filepath", label="Drag & drop a file or click to upload")
-                with gr.TabItem("From URL", id="url_tab"):
+                with gr.TabItem("From URL"):
                     image_url_input = gr.Textbox(
                         label="Image URL",
                         placeholder="https://example.com/image.jpg",
@@ -288,8 +239,7 @@ with gr.Blocks(
 
             run_btn = gr.Button("Start Analysis", variant="primary", scale=2)
 
-        # Column 2: Outputs
-        with gr.Column(scale=2, min_width=500) as right_col:
+        with gr.Column(scale=2, min_width=500):
             gr.Markdown("## 📊 Step 3: Review Results")
             verdict_output = gr.HTML(label="Final Verdict")
             label_output = gr.Label(label="Classification Scores", num_top_classes=4, show_label=True)
@@ -298,80 +248,43 @@ with gr.Blocks(
             with gr.Accordion("Show Raw JSON Output", open=False):
                 json_output = gr.JSON(label="Model Output (JSON)")
 
-    # Full-width Examples Gallery section
     gr.Markdown("## 🎯 Try an Example (click an image)")
     gallery_items = [[url, caption] for (url, _model, caption) in EXAMPLE_ITEMS]
-    examples_gallery_mobile = gr.Gallery(
+    examples_gallery = gr.Gallery(
         label="Try an Example",
         value=gallery_items,
-        columns=2,
+        columns=[2, 4],
         height="auto",
         allow_preview=False,
-        elem_id="examples-gallery-mobile",
-    )
-    examples_gallery_desktop = gr.Gallery(
-        label=None,
-        value=gallery_items,
-        columns=4,
-        height="auto",
-        allow_preview=False,
-        elem_id="examples-gallery-desktop",
     )
 
-    # Status label under galleries
-    status_md = gr.Markdown("Last analyse: —", elem_id="last-example-status")
-
-    # When a gallery image is selected, run analysis and update outputs + inputs + status
-    for gallery in (examples_gallery_mobile, examples_gallery_desktop):
-        gallery.select(
-            fn=run_example_by_index,
-            outputs=[
-                verdict_output,
-                label_output,
-                markdown_output,
-                json_output,
-                model_choice,
-                image_url_input,
-                status_md,
-            ],
-        )
-
-    # Interactive Event Listeners
+    status_md = gr.Markdown("Last analysed: —", elem_id="last-example-status")
+
+    examples_gallery.select(
+        fn=run_example_by_index,
+        outputs=[
+            verdict_output,
+            label_output,
+            markdown_output,
+            json_output,
+            model_choice,
+            image_url_input,
+            status_md,
+        ],
+    )
 
-    # When the analysis button is clicked
     run_btn.click(
         fn=analyze_image_with_status,
         inputs=[image_input, image_url_input, model_choice],
         outputs=[verdict_output, label_output, markdown_output, json_output, status_md],
     )
 
-    # Clear the other input when one changes (avoid relying on Tabs.select on some Gradio versions)
-    def _clear_url_on_image_change(_img):
-        # Keep image as-is, clear URL
-        return gr.update(), gr.update(value="")
-
-    def _clear_image_on_url_change(_url):
-        # Clear uploaded image, keep URL as-is
-        return gr.update(value=None), gr.update()
-
-    image_input.change(
-        fn=_clear_url_on_image_change,
-        inputs=[image_input],
-        outputs=[image_input, image_url_input],
-    )
-    image_url_input.change(
-        fn=_clear_image_on_url_change,
-        inputs=[image_url_input],
-        outputs=[image_input, image_url_input],
-    )
-
     gr.HTML("""
-    <div style=\"text-align: center; margin-top: 20px; color: #888;\">
+    <div style="text-align: center; margin-top: 20px; color: #888;">
         <p>Developed by Viddexa.</p>
     </div>
     """)
 
-# Create an 'examples' directory and download a sample image if it doesn't exist
 if not os.path.exists("examples"):
     os.makedirs("examples")
     print("Created 'examples' directory.")