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Update app.py
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app.py
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@@ -4,7 +4,7 @@ import os
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from dotenv import load_dotenv
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from simple_salesforce import Salesforce
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from datetime import datetime
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import
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import shutil
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# Load environment variables
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@@ -32,14 +32,26 @@ except Exception as e:
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# Valid milestones
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VALID_MILESTONES = ["Foundation", "Walls Erected", "Planning", "Completed"]
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def mock_ai_model(image):
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img = image.convert("RGB")
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max_size = 1024
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img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
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return milestone, completion_percent, confidence_score
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# Gradio function
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from dotenv import load_dotenv
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from simple_salesforce import Salesforce
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from datetime import datetime
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import hashlib
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import shutil
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# Load environment variables
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# Valid milestones
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VALID_MILESTONES = ["Foundation", "Walls Erected", "Planning", "Completed"]
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# Updated deterministic AI prediction based on image hash
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def mock_ai_model(image):
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img = image.convert("RGB")
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max_size = 1024
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img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
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# Convert image bytes to a hash value
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img_bytes = img.tobytes()
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img_hash = int(hashlib.sha256(img_bytes).hexdigest(), 16)
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# Use the hash to deterministically pick milestone and percentages
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milestone_index = img_hash % len(VALID_MILESTONES)
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completion_choices = [10, 30, 50, 80, 100]
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completion_index = (img_hash // 10) % len(completion_choices)
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confidence_raw = 0.85 + ((img_hash % 1000) / 1000) * (0.95 - 0.85)
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confidence_score = round(confidence_raw, 2)
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milestone = VALID_MILESTONES[milestone_index]
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completion_percent = completion_choices[completion_index]
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return milestone, completion_percent, confidence_score
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# Gradio function
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