Upload app.py

app.py

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+import cv2 as cv
+import numpy as np
+import gradio as gr
+
+# Filter Functions
+def apply_filter(image, filter_type):
+    if filter_type == "Gray":
+        return cv.cvtColor(image, cv.COLOR_BGR2GRAY)
+    elif filter_type == "Sepia":
+        sepia_filter = np.array([[0.272, 0.534, 0.131],
+                                 [0.349, 0.686, 0.168],
+                                 [0.393, 0.769, 0.189]])
+        sepia_image = cv.transform(image, sepia_filter)
+        return np.clip(sepia_image, 0, 255)
+    elif filter_type == "Invert":
+        return cv.bitwise_not(image)
+    elif filter_type == "Blur":
+        return cv.GaussianBlur(image, (15, 15), 0)
+    elif filter_type == "Sharpen":
+        kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
+        return cv.filter2D(image, -1, kernel)
+    elif filter_type == "Edge Detection":
+        return cv.Canny(image, 100, 200)
+    else:
+        return image
+
+# Rotation Function
+def rotate_image(image, angle):
+    (h, w) = image.shape[:2]
+    center = (w // 2, h // 2)
+    matrix = cv.getRotationMatrix2D(center, angle, 1.0)
+    rotated_image = cv.warpAffine(image, matrix, (w, h))
+    return rotated_image
+
+# Brightness and Contrast Adjustment
+def adjust_brightness_contrast(image, brightness=0, contrast=0):
+    beta = brightness - 128
+    alpha = contrast / 128 + 1
+    adjusted = cv.convertScaleAbs(image, alpha=alpha, beta=beta)
+    return adjusted
+
+# Resize Function
+def resize_image(image, scale_percent):
+    width = int(image.shape[1] * scale_percent / 100)
+    height = int(image.shape[0] * scale_percent / 100)
+    resized = cv.resize(image, (width, height), interpolation=cv.INTER_AREA)
+    return resized
+
+# Crop Function
+def crop_image(image, x, y, width, height):
+    return image[y:y+height, x:x+width]
+
+# Gradio function
+def process_image(image, filter_type, rotation_angle, brightness, contrast, scale_percent, crop_x, crop_y, crop_width, crop_height):
+    image = np.array(image)  # Convert Gradio image to OpenCV format
+    filtered_image = apply_filter(image, filter_type)
+    rotated_image = rotate_image(filtered_image, rotation_angle)
+    adjusted_image = adjust_brightness_contrast(rotated_image, brightness, contrast)
+    resized_image = resize_image(adjusted_image, scale_percent)
+    cropped_image = crop_image(resized_image, crop_x, crop_y, crop_width, crop_height)
+    return cropped_image
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Advanced Photo Editing Tool")
+
+    with gr.Row():
+        image_input = gr.Image(type="pil", label="Upload an Image")
+
+    with gr.Row():
+        filter_type = gr.Radio(["Gray", "Sepia", "Invert", "Original", "Blur", "Sharpen", "Edge Detection"], label="Filter Type")
+        rotation_angle = gr.Slider(0, 360, step=1, label="Rotation Angle")
+        brightness = gr.Slider(0, 255, step=1, label="Brightness")
+        contrast = gr.Slider(0, 255, step=1, label="Contrast")
+        scale_percent = gr.Slider(10, 200, step=10, label="Scale (%)")
+    
+    with gr.Row():
+        crop_x = gr.Slider(0, 500, step=1, label="Crop X")
+        crop_y = gr.Slider(0, 500, step=1, label="Crop Y")
+        crop_width = gr.Slider(10, 500, step=1, label="Crop Width")
+        crop_height = gr.Slider(10, 500, step=1, label="Crop Height")
+    
+    image_output = gr.Image(label="Resulting Image")
+    gr.Button("Process").click(process_image, inputs=[image_input, filter_type, rotation_angle, brightness, contrast, scale_percent, crop_x, crop_y, crop_width, crop_height], outputs=image_output)
+
+# Launch the demo
+if __name__ == "__main__":
+    demo.launch()