Create app.py

app.py

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+import cv2 as cv
+import numpy as np
+import gradio as gr
+
+def apply_gaussian_blur(frame, density):
+    ksize = int(density) * 2 + 1
+    return cv.GaussianBlur(frame, (ksize, ksize), 0)
+
+def apply_sharpening_filter(frame, density):
+    kernel = np.array([[-1, -1, -1], [-1, 8 * density, -1], [-1, -1, -1]])
+    return cv.filter2D(frame, -1, kernel)
+
+def apply_edge_detection(frame, density):
+    return cv.Canny(frame, 100, 100 * density)
+
+def apply_invert_filter(frame, density):
+    return cv.bitwise_not(frame)
+
+def adjust_brightness_contrast(frame, density):
+    alpha = 1.0 + density / 50.0
+    beta = density * 2
+    return cv.convertScaleAbs(frame, alpha=alpha, beta=beta)
+
+def apply_grayscale_filter(frame, density):
+    return cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
+
+def apply_sepia_filter(frame, density):
+    sepia_filter = np.array([[0.272 * density, 0.534 * density, 0.131 * density],
+                             [0.349 * density, 0.686 * density, 0.168 * density],
+                             [0.393 * density, 0.769 * density, 0.189 * density]])
+    return cv.transform(frame, sepia_filter)
+
+def apply_sketch_filter(frame, density):
+    gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
+    inv = cv.bitwise_not(gray)
+    blur = cv.GaussianBlur(inv, (21, 21), 0)
+    sketch = cv.divide(gray, 255 - blur, scale=256)
+    return cv.multiply(sketch, density)
+
+def apply_cartoon_filter(frame, density):
+    gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
+    blur = cv.medianBlur(gray, 7)
+    edges = cv.adaptiveThreshold(blur, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY, 9, 10)
+    color = cv.bilateralFilter(frame, 9, 300, 300)
+    cartoon = cv.bitwise_and(color, color, mask=edges)
+    return cv.multiply(cartoon, density)
+
+def apply_pixelate_filter(frame, density):
+    pixel_size = int(density) + 1
+    h, w = frame.shape[:2]
+    temp = cv.resize(frame, (w // pixel_size, h // pixel_size), interpolation=cv.INTER_LINEAR)
+    return cv.resize(temp, (w, h), interpolation=cv.INTER_NEAREST)
+
+def apply_emboss_filter(frame, density):
+    kernel = np.array([[-2, -1, 0], [-1, 1 * density, 1], [0, 1, 2]])
+    return cv.filter2D(frame, -1, kernel)
+
+def apply_brightness_contrast_adjustment(frame, density):
+    return adjust_brightness_contrast(frame, density)
+
+def apply_sepia_tone(frame, density):
+    return apply_sepia_filter(frame, density)
+
+
+def apply_filter(input_image, filter_type, density):
+
+    frame = np.array(input_image)
+
+    if filter_type == "Gaussian Blur":
+        result = apply_gaussian_blur(frame, density)
+    elif filter_type == "Sharpen":
+        result = apply_sharpening_filter(frame, density)
+    elif filter_type == "Edge Detection":
+        result = apply_edge_detection(frame, density)
+    elif filter_type == "Invert":
+        result = apply_invert_filter(frame, density)
+    elif filter_type == "Brightness":
+        result = adjust_brightness_contrast(frame, density)
+    elif filter_type == "GrayScale":
+        result = apply_grayscale_filter(frame, density)
+    elif filter_type == "Sepia":
+        result = apply_sepia_filter(frame, density)
+    elif filter_type == "Sketch":
+        result = apply_sketch_filter(frame, density)
+    elif filter_type == "Cartoon":
+        result = apply_cartoon_filter(frame, density)
+    elif filter_type == "Pixelate":
+        result = apply_pixelate_filter(frame, density)
+    elif filter_type == "Emboss":
+        result = apply_emboss_filter(frame, density)
+    elif filter_type == "Brightness/Contrast":
+        result = apply_brightness_contrast_adjustment(frame, density)
+    elif filter_type == "Sepia Tone":
+        result = apply_sepia_tone(frame, density)
+    else:
+        result = frame
+
+    return result
+
+with gr.Blocks(css="""
+    #filter-dropdown {
+        width: 300px;
+        margin: 0 auto;
+    }
+    #apply-button {
+        background-color: #8B4513;
+        color: white;
+        font-weight: bold;
+        margin-top: 20px;
+    }
+    #apply-button:hover {
+        background-color: #8B4513;
+    }
+    #input-image, #output-image {
+        width: 100%;
+        border-radius: 10px;
+    }
+    h1 {
+        text-align: center;
+        color: #8B4513;
+    }
+    p {
+        text-align: center;
+        font-size: 20px;
+    }
+""") as demo:
+
+    gr.Markdown("""
+        <h1>🖼️ Image Filter Application  🖼️</h1>
+        <p>Select a filter and apply it to your image :) Enjoy!</p>
+    """)
+
+    with gr.Row():
+        with gr.Column():
+
+            filter_type = gr.Radio(
+                label="Choose a filter:",
+                choices=["Gaussian Blur", "Sharpen", "Edge Detection", "Invert", "Brightness", "GrayScale", "Sepia", "Sketch", "Cartoon", "Pixelate", "Emboss", "Brightness/Contrast", "Sepia Tone"],
+                value="Gaussian Blur",
+                elem_id="filter-radio"
+            )
+
+            density_slider = gr.Slider(
+                minimum=1,
+                maximum=5,
+                step=0.1,
+                label="Filter Intensity (Density)",
+                value=3,
+                elem_id="density-slider"
+            )
+
+            input_image = gr.Image(label="Upload Image", elem_id="input-image")
+
+            apply_button = gr.Button("Apply Filter", elem_id="apply-button")
+
+        with gr.Column():
+            output_image = gr.Image(label="Filtered Image", elem_id="output-image")
+
+    apply_button.click(fn=apply_filter, inputs=[input_image, filter_type, density_slider], outputs=output_image)
+
+demo.launch(share=True)