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| import gradio as gr | |
| import cv2 | |
| from cv2 import dnn_superres | |
| import sys | |
| from os.path import exists | |
| FILE_PATH = "butterfly.png" | |
| # increase the size of the picture with a factor of 3 | |
| factor = 3 | |
| # Create an SR object | |
| sr = dnn_superres.DnnSuperResImpl_create() | |
| # Read image | |
| image = cv2.imread(FILE_PATH) | |
| # Read the desired model | |
| path = "models/FSRCNN_x" + str(factor) + ".pb" | |
| sr.readModel(path) | |
| # Set the desired model and scale to get correct pre- and post-processing | |
| sr.setModel("fsrcnn", factor) | |
| # Upscale the image | |
| result = sr.upsample(image) | |
| # Save the image | |
| cv2.imwrite("./upscaled.png", result) | |
| # def greet(name): | |
| # return "Hello " + name + "!!" | |
| # iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| # iface.launch() | |