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Runtime error
| import gradio as gr | |
| import cv2 | |
| import requests | |
| import os | |
| from ultralyticsplus import YOLO, render_result | |
| file_urls = [ | |
| 'https://huggingface.co/spaces/foduucom/CandleStickScan-Stock-trading-yolov8/resolve/main/test/-2022-06-28-12-35-50_png.rf.8dee4bb645ea8b5036721b830d2636b1.jpg', | |
| 'https://huggingface.co/spaces/foduucom/CandleStickScan-Stock-trading-yolov8/resolve/main/test/-2022-06-28-12-45-10_png.rf.8b9177546e62a2422ad603b16f1f50b9.jpg', | |
| 'https://www.dropbox.com/s/7sjfwncffg8xej2/video_7.mp4?dl=1' | |
| ] | |
| description=""" 🕯️ Introducing CandleScan by Foduu AI 🕯️ | |
| Unleash the power of precise pattern recognition with CandleScan, your ultimate companion for deciphering intricate candlestick formations in the world of trading. 📊📈 | |
| Unlock the secrets of successful trading by effortlessly identifying crucial candlestick patterns such as 'Head and Shoulders Bottom', 'Head and Shoulders Top', 'M-Head', 'StockLine', 'Triangle', and 'W-Bottom'. 📉📈 | |
| Powered by the cutting-edge technology of Foduu AI, CandleScan is your expert guide to navigating the complexities of the market. Whether you're an experienced trader or a novice investor, our app empowers you to make informed decisions with confidence. 💼💰 | |
| But that's not all! CandleScan is just the beginning. If you're hungry for more pattern recognition prowess, simply reach out to us at info@foddu.com. Our dedicated team is ready to assist you in expanding your trading horizons by integrating additional pattern recognition features. 📬📲 | |
| Show your appreciation for this space-age tool by hitting the 'Like' button and start embarking on a journey towards trading mastery with CandleScan! 🚀🕯️📈 | |
| 📧 Contact us: info@foddu.com | |
| 👍 Like | """ | |
| def download_file(url, save_name): | |
| url = url | |
| if not os.path.exists(save_name): | |
| file = requests.get(url) | |
| open(save_name, 'wb').write(file.content) | |
| for i, url in enumerate(file_urls): | |
| if 'mp4' in file_urls[i]: | |
| download_file( | |
| file_urls[i], | |
| f"video.mp4" | |
| ) | |
| # else: | |
| # download_file( | |
| # file_urls[i], | |
| # f"image_{i}.jpg" | |
| # ) | |
| model = YOLO('foduucom/stockmarket-pattern-detection-yolov8') | |
| path = [['test/test1.jpg'], ['test/test2.jpg']] | |
| video_path = [['video.mp4']] | |
| def show_preds_image(image_path): | |
| image = cv2.imread(image_path) | |
| outputs = model.predict(source=image_path) | |
| results = outputs[0].cpu().numpy() | |
| for i, det in enumerate(results.boxes.xyxy): | |
| cv2.rectangle( | |
| image, | |
| (int(det[0]), int(det[1])), | |
| (int(det[2]), int(det[3])), | |
| color=(0, 0, 255), | |
| thickness=2, | |
| lineType=cv2.LINE_AA | |
| ) | |
| return cv2.cvtColor(image, cv2.COLOR_BGR2RGB) | |
| inputs_image = [ | |
| gr.components.Image(type="filepath", label="Input Image"), | |
| ] | |
| outputs_image = [ | |
| gr.components.Image(type="numpy", label="Output Image"), | |
| ] | |
| interface_image = gr.Interface( | |
| fn=show_preds_image, | |
| inputs=inputs_image, | |
| outputs=outputs_image, | |
| title="CandleStickScan: Pattern Recognition for Trading Success", | |
| descripiton=description, | |
| examples=path, | |
| cache_examples=False, | |
| ) | |
| def show_preds_video(video_path): | |
| cap = cv2.VideoCapture(video_path) | |
| while(cap.isOpened()): | |
| ret, frame = cap.read() | |
| if ret: | |
| frame_copy = frame.copy() | |
| outputs = model.predict(source=frame) | |
| results = outputs[0].cpu().numpy() | |
| for i, det in enumerate(results.boxes.xyxy): | |
| cv2.rectangle( | |
| frame_copy, | |
| (int(det[0]), int(det[1])), | |
| (int(det[2]), int(det[3])), | |
| color=(0, 0, 255), | |
| thickness=2, | |
| lineType=cv2.LINE_AA | |
| ) | |
| yield cv2.cvtColor(frame_copy, cv2.COLOR_BGR2RGB) | |
| inputs_video = [ | |
| gr.components.Video(type="filepath", label="Input Video"), | |
| ] | |
| outputs_video = [ | |
| gr.components.Image(type="numpy", label="Output Image"), | |
| ] | |
| interface_video = gr.Interface( | |
| fn=show_preds_video, | |
| inputs=inputs_video, | |
| outputs=outputs_video, | |
| title="CandleStickScan: Pattern Recognition for Trading Success", | |
| descripiton=description, | |
| examples=video_path, | |
| cache_examples=False, | |
| ) | |
| gr.TabbedInterface( | |
| [interface_image, interface_video], | |
| tab_names=['Image inference', 'Video inference'] | |
| ).queue().launch() |