Add video sample
Browse files
app.py
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@@ -1,19 +1,9 @@
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import gradio as gr
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import cv2
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import requests
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import os
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from ultralytics import YOLO
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# Function to download files
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def fetch_file(url, filename):
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if not os.path.exists(filename):
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response = requests.get(url)
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with open(filename, "wb") as file:
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file.write(response.content)
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# Function to process and display predictions on images
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def process_image(image_path):
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img = cv2.imread(image_path)
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inputs=[gr.components.Image(type="filepath", label="Select Image")],
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outputs=[gr.components.Image(type="numpy", label="Processed Image")],
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title="Tomato Ripeness Detection",
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examples=["
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cache_examples=False,
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)
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@@ -90,25 +80,11 @@ video_interface = gr.Interface(
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inputs=[gr.components.Video(label="Select Video")],
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outputs=[gr.components.Image(type="numpy", label="Processed Frame")],
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title="Tomato Ripeness Detection in Video",
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examples=["
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cache_examples=False,
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)
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if __name__ == "__main__":
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# URLs for image and video files
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media_urls = [
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"https://cdn.pixabay.com/photo/2021/04/03/00/39/tomatoes-6146243_640.jpg",
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"https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQHDLF2oUAlSLcxcxrRKz4ud0LKP5S7doeWRA&s",
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"https://freerangestock.com/sample/133867/cherry-tomatoes-with-green-leaves.jpg"
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]
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# Downloading media files
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for index, url in enumerate(media_urls):
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if url.endswith(".mp4"):
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fetch_file(url, "downloaded_video.mp4")
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else:
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fetch_file(url, f"downloaded_image_{index}.jpg")
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# Create a tabbed interface for both image and video processing
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gr.TabbedInterface(
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[image_interface, video_interface],
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import gradio as gr
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import cv2
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from ultralytics import YOLO
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# Function to process and display predictions on images
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def process_image(image_path):
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img = cv2.imread(image_path)
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inputs=[gr.components.Image(type="filepath", label="Select Image")],
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outputs=[gr.components.Image(type="numpy", label="Processed Image")],
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title="Tomato Ripeness Detection",
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examples=["samples/image_0.jpg", "samples/image_1.jpg", "samples/image_1.jpg"],
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cache_examples=False,
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)
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inputs=[gr.components.Video(label="Select Video")],
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outputs=[gr.components.Image(type="numpy", label="Processed Frame")],
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title="Tomato Ripeness Detection in Video",
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examples=["samples/video.mp4"],
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cache_examples=False,
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)
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if __name__ == "__main__":
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# Create a tabbed interface for both image and video processing
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gr.TabbedInterface(
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[image_interface, video_interface],
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downloaded_image_0.jpg β samples/image_0.jpg
RENAMED
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File without changes
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downloaded_image_1.jpg β samples/image_1.jpg
RENAMED
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File without changes
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downloaded_image_2.jpg β samples/image_2.jpg
RENAMED
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File without changes
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samples/video.mp4
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:439a7d87b9aaf5b49d87e5bb6d4b423860f570cfdd4ec870a4b1e4b79b1fdd50
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size 3661477
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