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Parent(s):
Duplicate from Khaled27/Naptah
Browse filesCo-authored-by: Khaled Mohamed <Khaled27@users.noreply.huggingface.co>
- .gitattributes +34 -0
- README.md +14 -0
- app.py +50 -0
- myModel/config.json +57 -0
- myModel/pytorch_model.bin +3 -0
- requirements.txt +49 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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title: Naptah
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emoji: 🏆
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colorFrom: yellow
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colorTo: purple
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sdk: streamlit
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sdk_version: 1.19.0
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app_file: app.py
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pinned: false
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license: other
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duplicated_from: Khaled27/Naptah
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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from flask import Flask, request
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from transformers import AutoModelForImageClassification
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from transformers import AutoImageProcessor
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from PIL import Image
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import torch
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app = Flask(__name__)
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model = AutoModelForImageClassification.from_pretrained(
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'./myModel')
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image_processor = AutoImageProcessor.from_pretrained(
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"google/vit-base-patch16-224-in21k")
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@app.route('/upload_image', methods=['POST'])
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def upload_image():
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# Get the image file from the request
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image_file = request.files['image']
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# Save the image file to a desired location on the server
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image_path = "assets/img.jpg"
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image_file.save(image_path)
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# You can perform additional operations with the image here
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# ...
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return 'Image uploaded successfully'
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@app.route('/get_text', methods=['GET'])
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def get_text():
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image = Image.open('assets/img.jpg')
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inputs = image_processor(image, return_tensors="pt")
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with torch.no_grad():
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logits = model(**inputs).logits
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predicted_label = logits.argmax(-1).item()
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disease = model.config.id2label[predicted_label]
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return disease
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print('upload_image()')
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# if __name__ == '__app__':
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# app.run(host='192.168.1.7', port=5000 )
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if __name__ == '__app__':
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app.run( host='0.0.0.0',port=7860)
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myModel/config.json
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{
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"_name_or_path": "my_model",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "Pepper__bell___Bacterial_spot",
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"1": "Pepper__bell___healthy",
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"2": "Potato___Early_blight",
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"3": "Potato___Late_blight",
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"4": "Potato___healthy",
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"5": "Tomato_Bacterial_spot",
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"6": "Tomato_Early_blight",
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"7": "Tomato_Late_blight",
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"8": "Tomato_Leaf_Mold",
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"9": "Tomato_Septoria_leaf_spot",
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"10": "Tomato_Spider_mites_Two_spotted_spider_mite",
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"11": "Tomato__Target_Spot",
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"12": "Tomato__Tomato_YellowLeaf__Curl_Virus",
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"13": "Tomato__Tomato_mosaic_virus",
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"14": "Tomato_healthy"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Pepper__bell___Bacterial_spot": "0",
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"Pepper__bell___healthy": "1",
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"Potato___Early_blight": "2",
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"Potato___Late_blight": "3",
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"Potato___healthy": "4",
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"Tomato_Bacterial_spot": "5",
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"Tomato_Early_blight": "6",
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"Tomato_Late_blight": "7",
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"Tomato_Leaf_Mold": "8",
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"Tomato_Septoria_leaf_spot": "9",
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"Tomato_Spider_mites_Two_spotted_spider_mite": "10",
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"Tomato__Target_Spot": "11",
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"Tomato__Tomato_YellowLeaf__Curl_Virus": "12",
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"Tomato__Tomato_mosaic_virus": "13",
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"Tomato_healthy": "14"
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.26.1"
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}
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myModel/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:319df356e382a14d3cee2e0c0bf21c99faaf8f3e7017ef03c20adc01dcb6cc41
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size 343305965
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requirements.txt
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altair==4.1.0
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autopep8==1.7.0
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biopython==1.79
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blinker==1.6.2
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certifi==2023.5.7
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charset-normalizer==3.1.0
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click==8.1.3
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colorama==0.4.6
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contourpy==1.0.6
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cycler==0.11.0
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docopt==0.6.2
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filelock==3.12.0
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Flask==2.3.2
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fonttools==4.38.0
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fsspec==2023.5.0
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huggingface-hub==0.14.1
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idna==3.4
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itsdangerous==2.1.2
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Jinja2==3.1.2
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kiwisolver==1.4.4
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MarkupSafe==2.1.2
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matplotlib==3.6.1
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mpmath==1.3.0
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networkx==3.1
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numpy==1.23.4
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opencv-python==4.6.0.66
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packaging==21.3
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pandas==1.5.3
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Pillow==9.3.0
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pipreqs==0.4.13
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pycodestyle==2.9.1
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pyparsing==3.0.9
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python-dateutil==2.8.2
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pytz==2022.7.1
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PyYAML==6.0
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regex==2023.5.5
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requests==2.31.0
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scipy==1.9.3
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six==1.16.0
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sympy==1.12
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tokenizers==0.13.3
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toml==0.10.2
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torch==2.0.1
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tqdm==4.65.0
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transformers==4.29.2
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typing_extensions==4.5.0
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urllib3==2.0.2
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Werkzeug==2.3.4
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yarg==0.1.9
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