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worked on app
Browse files- .gitignore +5 -0
- app.py +59 -0
- requirements.txt +47 -0
.gitignore
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flagged/
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*.pt
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*.png
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*.jpg
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gradio_cached_examples/
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app.py
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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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import torch
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import ultralytics
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file_urls = [
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'https://www.dropbox.com/s/bc9r8n7919cbc77/test-image.jpg?dl=0',
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'https://www.dropbox.com/s/fkmzgdm6okdzxdk/test-image-2.jpg?dl=0',
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]
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def download_file(url, save_name):
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url = url
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if not os.path.exists(save_name):
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file = requests.get(url)
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open(save_name, 'wb').write(file.content)
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for i, url in enumerate(file_urls):
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download_file(
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file_urls[i],
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f"image_{i}.jpg"
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)
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model = torch.hub.load("ultralytics/yolov5", "custom", path="../yolov5_0.65map_exp7_best.pt",
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force_reload=False)
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path = [['image_0.jpg'], ['image_1.jpg']]
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def show_preds_image(image_path):
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image = cv2.imread(image_path)
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outputs = model.predict(source=image_path)
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results = outputs[0].cpu().numpy()
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for i, det in enumerate(results.boxes.xyxy):
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cv2.rectangle(
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image,
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(int(det[0]), int(det[1])),
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(int(det[2]), int(det[3])),
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color=(0, 0, 255),
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thickness=2,
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lineType=cv2.LINE_AA
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)
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return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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inputs_image = [
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gr.components.Image(type="filepath", label="Input Image"),
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]
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outputs_image = [
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gr.components.Image(type="numpy", label="Output Image"),
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]
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interface_image = gr.Interface(
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fn=show_preds_image,
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inputs=inputs_image,
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outputs=outputs_image,
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title="Pothole detector",
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examples=path,
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cache_examples=False,
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)
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requirements.txt
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# Ultralytics requirements
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# Usage: pip install -r requirements.txt
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# Base ----------------------------------------
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hydra-core>=1.2.0
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matplotlib>=3.2.2
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numpy>=1.18.5
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opencv-python>=4.1.1
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Pillow>=7.1.2
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PyYAML>=5.3.1
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requests>=2.23.0
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scipy>=1.4.1
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torch>=1.7.0
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torchvision>=0.8.1
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tqdm>=4.64.0
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ultralytics
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# Logging -------------------------------------
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tensorboard>=2.4.1
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# clearml
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# comet
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# Plotting ------------------------------------
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pandas>=1.1.4
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seaborn>=0.11.0
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# Export --------------------------------------
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# coremltools>=6.0 # CoreML export
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# onnx>=1.12.0 # ONNX export
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# onnx-simplifier>=0.4.1 # ONNX simplifier
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# nvidia-pyindex # TensorRT export
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# nvidia-tensorrt # TensorRT export
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# scikit-learn==0.19.2 # CoreML quantization
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# tensorflow>=2.4.1 # TF exports (-cpu, -aarch64, -macos)
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# tensorflowjs>=3.9.0 # TF.js export
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# openvino-dev # OpenVINO export
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# Extras --------------------------------------
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ipython # interactive notebook
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psutil # system utilization
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thop>=0.1.1 # FLOPs computation
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# albumentations>=1.0.3
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# pycocotools>=2.0.6 # COCO mAP
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# roboflow
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# HUB -----------------------------------------
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GitPython>=3.1.24
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