Create app.py

app.py

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+
+
+import gradio as gr
+import cv2
+import numpy as np
+import cupy as cp
+
+# CUDA kernel for custom filter (example sharpening)
+custom_filter_kernel = cp.array([[0, -1, 0],
+                                 [-1, 5, -1],
+                                 [0, -1, 0]], dtype=cp.float32)
+
+def edge_detection_cuda(image):
+    img_gpu = cp.asarray(image, dtype=cp.uint8)
+    gray_gpu = cp.asarray(cv2.cvtColor(image, cv2.COLOR_RGB2GRAY))
+    edges_gpu = cv2.Canny(cp.asnumpy(gray_gpu), 100, 200)
+    return cv2.cvtColor(edges_gpu, cv2.COLOR_GRAY2RGB)
+
+def gaussian_blur_cuda(image):
+    img_gpu = cp.asarray(image, dtype=cp.float32)
+    blurred_gpu = cv2.GaussianBlur(cp.asnumpy(img_gpu), (15, 15), 0)
+    return blurred_gpu.astype(np.uint8)
+
+def custom_filter_cuda(image):
+    img_gpu = cp.asarray(image, dtype=cp.float32)
+    img_gpu = cv2.filter2D(cp.asnumpy(img_gpu), -1, cp.asnumpy(custom_filter_kernel))
+    return img_gpu.astype(np.uint8)
+
+def process_image(image, operation):
+    if image is None:
+        return None, None, None
+
+    edge_result = None
+    blur_result = None
+    custom_result = None
+
+    if operation == "All":
+        # Run operations in parallel using CUDA Streams
+        stream1 = cp.cuda.Stream()
+        stream2 = cp.cuda.Stream()
+        stream3 = cp.cuda.Stream()
+
+        with stream1:
+            edge_result = edge_detection_cuda(image)
+        with stream2:
+            blur_result = gaussian_blur_cuda(image)
+        with stream3:
+            custom_result = custom_filter_cuda(image)
+
+        stream1.synchronize()
+        stream2.synchronize()
+        stream3.synchronize()
+
+    elif operation == "Edge Detection":
+        edge_result = edge_detection_cuda(image)
+    elif operation == "Gaussian Blur":
+        blur_result = gaussian_blur_cuda(image)
+    elif operation == "Custom Filter":
+        custom_result = custom_filter_cuda(image)
+
+    return edge_result, blur_result, custom_result
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 🖼️ Parallel Image Processing with CUDA (GPU)")
+
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(type="numpy", label="Upload Image")
+            process_btn = gr.Button("Process Image", variant="primary")
+        with gr.Column():
+            operation = gr.Radio(["All", "Edge Detection", "Gaussian Blur", "Custom Filter"],
+                                 label="Choose Operation", value="All")
+
+    with gr.Row():
+        edge_output = gr.Image(label="Edge Detection Result")
+        blur_output = gr.Image(label="Gaussian Blur Result")
+        custom_output = gr.Image(label="Custom Filter Result")
+
+    process_btn.click(process_image, inputs=[image_input, operation],
+                      outputs=[edge_output, blur_output, custom_output])
+
+# Launch app
+demo.launch()