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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() | |