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Update app.py
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app.py
CHANGED
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@@ -35,8 +35,9 @@ def plot_img_bbox(img, target):
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cv2.putText(img, label, (xmin, ymin - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2)
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# Display the image with detections
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filename = 'pred.jpg'
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cv2.imwrite(filename, img)
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# transform image
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test_transforms = A.Compose([
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@@ -71,15 +72,18 @@ def predict(img) :
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nms_prediction = apply_nms(predictions, iou_thresh=0.1)
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plot_img_bbox(np.array(img), nms_prediction)
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pred = np.array(Image.open("pred.jpg"))
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# Calculate the prediction time
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pred_time = round(timer() - start_time, 5)
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# Return the prediction dictionary and prediction time
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return pred
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### 4. Gradio app ###
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# Create title, description and article strings
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@@ -89,13 +93,13 @@ article = "Created by data354."
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# Create examples list from "examples/" directory
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example_list = [["examples/" + example] for example in os.listdir("examples")]
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# Create the Gradio demo
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demo = gr.Interface(fn=predict, # mapping function from input to output
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inputs=gr.Image(type="pil"), # what are the inputs?
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outputs=
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gr.Number(label="Prediction time (s)")], # our fn has two outputs, therefore we have two outputs
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# Create examples list from "examples/" directory
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examples=example_list,
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title=title,
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description=description,
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cv2.putText(img, label, (xmin, ymin - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2)
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# Display the image with detections
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#filename = 'pred.jpg'
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#cv2.imwrite(filename, img)
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return img
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# transform image
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test_transforms = A.Compose([
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nms_prediction = apply_nms(predictions, iou_thresh=0.1)
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pred = plot_img_bbox(np.array(img), nms_prediction)
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#pred = np.array(Image.open("pred.jpg"))
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# Calculate the prediction time
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pred_time = round(timer() - start_time, 5)
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# Return the prediction dictionary and prediction time
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return pred
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image = gr.components.Image()
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out_im = gr.components.Image()
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### 4. Gradio app ###
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# Create title, description and article strings
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# Create examples list from "examples/" directory
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example_list = [["examples/" + example] for example in os.listdir("examples")]
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#[gr.Label(label="Predictions"), # what are the outputs?
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#gr.Number(label="Prediction time (s)")], # our fn has two outputs, therefore we have two outputs
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# Create examples list from "examples/" directory
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# Create the Gradio demo
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demo = gr.Interface(fn=predict, # mapping function from input to output
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inputs=gr.Image(type="pil"), # what are the inputs?
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outputs=out_im
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examples=example_list,
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title=title,
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description=description,
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