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Create package.py
Browse files- package.py +60 -0
package.py
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import requests
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import matplotlib.pyplot as plt
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from PIL import Image
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import csv
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import os
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API_URL = "https://api-inference.huggingface.co/models/OttoYu/Tree-Inspection"
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headers = {"Authorization": "Bearer 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"}
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def TreeAI(image_path):
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def query(filename):
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with open(filename, "rb") as f:
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data = f.read()
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response = requests.post(API_URL, headers=headers, data=data)
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return response.json()
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output = query(image_path)
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if "error" in output:
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print("Error:", output["error"])
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else:
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for result in output:
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label = result["label"]
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confidence = result["score"]
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print("Prediction:", label, ",", confidence, "%")
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image = Image.open(image_path)
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plt.imshow(image)
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plt.axis('off')
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plt.show()
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def TreeAI_Batch(folder_path, output_csv):
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image_paths = []
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for filename in os.listdir(folder_path):
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if filename.endswith((".jpg", ".jpeg", ".png")):
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image_paths.append(os.path.join(folder_path, filename))
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num_images = len(image_paths)
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results = []
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for i, image_path in enumerate(image_paths):
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print(f"Processing image {i+1}/{num_images}...")
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output = query(image_path)
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if "error" in output:
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print("Error:", output["error"])
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else:
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for result in output:
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filename = os.path.basename(image_path)
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label = result["label"]
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confidence = result["score"]
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results.append([filename, label, confidence])
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with open(output_csv, "w", newline="") as csvfile:
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writer = csv.writer(csvfile)
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writer.writerow(["Filename", "Prediction", "Confidence"])
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writer.writerows(results)
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