Upload folder using huggingface_hub

app.py

@@ -0,0 +1,197 @@
+import gradio as gr
+import os
+from PIL import Image
+import numpy as np
+
+# Custom theme for professional UI design
+custom_theme = gr.themes.Soft(
+    primary_hue="blue",
+    secondary_hue="indigo",
+    neutral_hue="slate",
+    font=gr.themes.GoogleFont("Inter"),
+    text_size="lg",
+    spacing_size="lg",
+    radius_size="md"
+).set(
+    button_primary_background_fill="*primary_600",
+    button_primary_background_fill_hover="*primary_700",
+    block_title_text_weight="600",
+)
+
+def process_single_image(image, prompt):
+    """
+    Process a single image with the given prompt
+    """
+    # Convert image to numpy array
+    img_array = np.array(image)
+
+    # Here you would add your actual processing logic
+    # For demonstration, we'll just return the image with a watermark
+
+    # Create a simple watermark with the prompt text
+    result_img = Image.fromarray(img_array)
+    result_img = add_watermark(result_img, prompt)
+
+    return result_img
+
+def add_watermark(image, text):
+    """
+    Add watermark text to an image
+    """
+    # Create a copy of the image
+    img_copy = image.copy()
+
+    # Create a drawing context
+    draw = ImageDraw.Draw(img_copy)
+
+    # Get image dimensions
+    width, height = img_copy.size
+
+    # Set font and text position
+    try:
+        font = ImageFont.truetype("arial.ttf", 30)
+    except:
+        font = ImageFont.load_default()
+
+    # Calculate text size and position
+    text_width, text_height = draw.textsize(text, font=font)
+    position = (width - text_width - 10, height - text_height - 10)
+
+    # Add semi-transparent background for text
+    draw.rectangle(
+        [position[0] - 5, position[1] - 5,
+         position[0] + text_width + 5, position[1] + text_height + 5],
+        fill=(255, 255, 255, 150)
+    )
+
+    # Draw the text
+    draw.text(position, text, fill=(0, 0, 0), font=font)
+
+    return img_copy
+
+def process_batch(images, prompt):
+    """
+    Process multiple images with the same prompt
+    """
+    results = []
+    for image in images:
+        if image is not None:
+            result = process_single_image(image, prompt)
+            results.append(result)
+        else:
+            results.append(None)
+    return results
+
+def process_batch_files(image_files, prompt):
+    """
+    Process multiple image files with the same prompt
+    """
+    results = []
+    for file_path in image_files:
+        try:
+            # Open the image file
+            with Image.open(file_path) as img:
+                result = process_single_image(img, prompt)
+                results.append(result)
+        except Exception as e:
+            print(f"Error processing {file_path}: {e}")
+            results.append(None)
+    return results
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# 🖼️ Batch Image Processor")
+    gr.Markdown("Built with [anycoder](https://huggingface.co/spaces/akhaliq/anycoder)")
+
+    with gr.Tabs():
+        # Single Image Processing Tab
+        with gr.Tab("Single Image"):
+            gr.Markdown("### Process a single image with your prompt")
+
+            with gr.Row():
+                with gr.Column():
+                    single_image_input = gr.Image(label="Upload Image", type="pil")
+                    single_prompt = gr.Textbox(label="Prompt", placeholder="Enter your processing prompt...")
+                    single_process_btn = gr.Button("Process Image", variant="primary")
+
+                with gr.Column():
+                    single_output = gr.Image(label="Processed Image")
+
+            single_process_btn.click(
+                fn=process_single_image,
+                inputs=[single_image_input, single_prompt],
+                outputs=single_output,
+                api_visibility="public"
+            )
+
+        # Batch Processing Tab
+        with gr.Tab("Batch Processing"):
+            gr.Markdown("### Process multiple images with the same prompt")
+
+            with gr.Row():
+                with gr.Column():
+                    batch_images_input = gr.Gallery(
+                        label="Upload Multiple Images",
+                        type="pil",
+                        height="auto"
+                    )
+                    batch_prompt = gr.Textbox(label="Prompt", placeholder="Enter your processing prompt...")
+                    batch_process_btn = gr.Button("Process All Images", variant="primary")
+
+                with gr.Column():
+                    batch_output = gr.Gallery(label="Processed Images")
+
+            batch_process_btn.click(
+                fn=process_batch,
+                inputs=[batch_images_input, batch_prompt],
+                outputs=batch_output,
+                api_visibility="public"
+            )
+
+        # File Batch Processing Tab
+        with gr.Tab("File Batch Processing"):
+            gr.Markdown("### Process multiple image files with the same prompt")
+
+            with gr.Row():
+                with gr.Column():
+                    file_batch_input = gr.File(
+                        label="Upload Image Files",
+                        file_count="multiple",
+                        file_types=["image"]
+                    )
+                    file_batch_prompt = gr.Textbox(label="Prompt", placeholder="Enter your processing prompt...")
+                    file_batch_process_btn = gr.Button("Process All Files", variant="primary")
+
+                with gr.Column():
+                    file_batch_output = gr.Gallery(label="Processed Images")
+
+            file_batch_process_btn.click(
+                fn=process_batch_files,
+                inputs=[file_batch_input, file_batch_prompt],
+                outputs=file_batch_output,
+                api_visibility="public"
+            )
+
+    # Examples section
+    gr.Markdown("## 📚 Examples")
+    examples = gr.Examples(
+        examples=[
+            ["https://gradio-builds.s3.amazonaws.com/assets/cheetah-003.jpg", "Wildlife processing"],
+            ["https://gradio-builds.s3.amazonaws.com/assets/TheCheethcat.jpg", "Animal detection"],
+            ["https://gradio-static-files.s3.amazonaws.com/world.mp4", "Video frame processing"]
+        ],
+        inputs=[single_image_input, single_prompt],
+        outputs=single_output,
+        cache_examples=True
+    )
+
+# Launch the application with custom theme and settings
+demo.launch(
+    theme=custom_theme,
+    footer_links=[
+        {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"},
+        {"label": "Gradio Documentation", "url": "https://gradio.app/docs"}
+    ],
+    show_error=True,
+    debug=False
+)

requirements.txt

@@ -0,0 +1,6 @@
+Pillow
+gradio>=6.0
+numpy
+requests
+scipy
+pandas