mirror of
https://github.com/gradio-app/gradio.git
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Merge branch 'abidlabs/similarity' of github.com:gradio-app/gradio into abidlabs/similarity
This commit is contained in:
commit
fd835d1a06
@ -48,7 +48,7 @@ var io_master_template = {
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output = output["data"];
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output = output["data"];
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this.target.find(".loading").addClass("invisible");
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this.target.find(".loading").addClass("invisible");
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this.target.find(".output_interfaces").css("opacity", 1);
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this.target.find(".output_interfaces").css("opacity", 1);
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this.order_mapping = sortWithIndices(output);
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this.order_mapping = sortWithIndices(output).reverse();
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callback();
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callback();
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})
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})
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},
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},
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@ -87,14 +87,18 @@ const image_input = {
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dest_height: dim,
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dest_height: dim,
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})
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})
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Webcam.attach(this.target.find(".webcam_box")[0]);
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Webcam.attach(this.target.find(".webcam_box")[0]);
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io.target.find(".webcam").click(function() {
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if (io.io_master.config.live) {
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Webcam.snap(function(image_data) {
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io.target.find(".webcam span").hide();
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io.target.find(".webcam").hide();
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} else {
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io.target.find(".image_display").removeClass("hide");
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io.target.find(".webcam").click(function() {
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io.set_image_data(image_data, /*update_editor=*/true);
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Webcam.snap(function(image_data) {
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io.state = "IMAGE_LOADED";
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io.target.find(".webcam").hide();
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});
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io.target.find(".image_display").removeClass("hide");
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})
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io.set_image_data(image_data, /*update_editor=*/true);
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io.state = "IMAGE_LOADED";
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});
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})
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}
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} else if (this.source == "canvas") {
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} else if (this.source == "canvas") {
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io.target.find(".sketchpad").removeClass("hide");
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io.target.find(".sketchpad").removeClass("hide");
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var dimension = Math.min(this.target.find(".canvas_holder").width(),
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var dimension = Math.min(this.target.find(".canvas_holder").width(),
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@ -156,12 +160,20 @@ const image_input = {
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io.io_master.input(io.id, this.image_data);
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io.io_master.input(io.id, this.image_data);
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}
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}
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} else if (this.source == "webcam") {
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} else if (this.source == "webcam") {
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if (!Webcam.loaded) {
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io.io_master.no_input();
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return;
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}
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Webcam.snap(function(image_data) {
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Webcam.snap(function(image_data) {
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io.target.find(".webcam").hide();
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if (io.io_master.config.live) {
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io.target.find(".image_display").removeClass("hide");
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io.io_master.input(io.id, image_data);
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io.set_image_data(image_data, /*update_editor=*/true);
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} else {
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io.state = "IMAGE_LOADED";
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io.target.find(".webcam").hide();
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io.io_master.input(io.id, image_data);
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io.target.find(".image_display").removeClass("hide");
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io.set_image_data(image_data, /*update_editor=*/true);
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io.state = "IMAGE_LOADED";
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io.io_master.input(io.id, image_data);
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}
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});
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});
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} else {
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} else {
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io.io_master.no_input();
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io.io_master.no_input();
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@ -1,7 +1,7 @@
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# Demo: (Image) -> (Label)
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# Demo: (Image) -> (Label)
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import gradio as gr
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import gradio as gr
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# import tensorflow as tf
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import tensorflow as tf
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import numpy as np
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import numpy as np
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from PIL import Image
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from PIL import Image
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@ -15,13 +15,12 @@ current_dir = os.path.dirname(os.path.realpath(__file__))
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with open(os.path.join(current_dir, "files/imagenet_labels.json")) as labels_file:
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with open(os.path.join(current_dir, "files/imagenet_labels.json")) as labels_file:
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labels = json.load(labels_file)
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labels = json.load(labels_file)
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# mobile_net = tf.keras.applications.MobileNetV2()
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mobile_net = tf.keras.applications.MobileNetV2()
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def image_classifier(im):
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def image_classifier(im):
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return 0
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arr = np.expand_dims(im, axis=0)
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arr = np.expand_dims(im, axis=0)
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# arr = tf.keras.applications.mobilenet.preprocess_input(arr)
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arr = tf.keras.applications.mobilenet.preprocess_input(arr)
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prediction = mobile_net.predict(arr).flatten()
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prediction = mobile_net.predict(arr).flatten()
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return {labels[i]: float(prediction[i]) for i in range(1000)}
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return {labels[i]: float(prediction[i]) for i in range(1000)}
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@ -38,4 +37,4 @@ iface = gr.Interface(image_classifier, image, label,
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])
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])
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if __name__ == "__main__":
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if __name__ == "__main__":
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iface.launch()
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iface.launch(share=True)
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@ -8,7 +8,7 @@ def snap(image):
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return np.flipud(image)
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return np.flipud(image)
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iface = gr.Interface(snap, gr.inputs.Image(shape=(100,100), image_mode="L", source="webcam"), "image")
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iface = gr.Interface(snap, gr.inputs.Image(shape=(100,100), image_mode="L", source="webcam"), "image", live=True)
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iface.test_launch()
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iface.test_launch()
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if __name__ == "__main__":
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if __name__ == "__main__":
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@ -87,14 +87,18 @@ const image_input = {
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dest_height: dim,
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dest_height: dim,
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})
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})
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Webcam.attach(this.target.find(".webcam_box")[0]);
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Webcam.attach(this.target.find(".webcam_box")[0]);
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io.target.find(".webcam").click(function() {
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if (io.io_master.config.live) {
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Webcam.snap(function(image_data) {
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io.target.find(".webcam span").hide();
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io.target.find(".webcam").hide();
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} else {
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io.target.find(".image_display").removeClass("hide");
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io.target.find(".webcam").click(function() {
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io.set_image_data(image_data, /*update_editor=*/true);
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Webcam.snap(function(image_data) {
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io.state = "IMAGE_LOADED";
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io.target.find(".webcam").hide();
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});
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io.target.find(".image_display").removeClass("hide");
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})
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io.set_image_data(image_data, /*update_editor=*/true);
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io.state = "IMAGE_LOADED";
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});
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})
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}
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} else if (this.source == "canvas") {
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} else if (this.source == "canvas") {
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io.target.find(".sketchpad").removeClass("hide");
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io.target.find(".sketchpad").removeClass("hide");
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var dimension = Math.min(this.target.find(".canvas_holder").width(),
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var dimension = Math.min(this.target.find(".canvas_holder").width(),
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@ -156,12 +160,20 @@ const image_input = {
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io.io_master.input(io.id, this.image_data);
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io.io_master.input(io.id, this.image_data);
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}
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}
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} else if (this.source == "webcam") {
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} else if (this.source == "webcam") {
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if (!Webcam.loaded) {
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io.io_master.no_input();
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return;
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}
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Webcam.snap(function(image_data) {
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Webcam.snap(function(image_data) {
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io.target.find(".webcam").hide();
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if (io.io_master.config.live) {
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io.target.find(".image_display").removeClass("hide");
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io.io_master.input(io.id, image_data);
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io.set_image_data(image_data, /*update_editor=*/true);
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} else {
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io.state = "IMAGE_LOADED";
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io.target.find(".webcam").hide();
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io.io_master.input(io.id, image_data);
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io.target.find(".image_display").removeClass("hide");
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io.set_image_data(image_data, /*update_editor=*/true);
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io.state = "IMAGE_LOADED";
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io.io_master.input(io.id, image_data);
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}
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});
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});
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} else {
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} else {
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io.io_master.no_input();
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io.io_master.no_input();
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