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83ee618 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 | from gait_analysis import EnhancedGaitAnalyzer
import os
import json
from generate_report import generate_markdown_report
from datetime import datetime
def main():
# Path to test.mp4
# The script is in backend/, test.mp4 is in root/ (../test.mp4)
video_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "atmin.mp4"))
print(f"Looking for video at: {video_path}")
if not os.path.exists(video_path):
print("Error: test.mp4 not found!")
return
print("Initializing EnhancedGaitAnalyzer...")
analyzer = EnhancedGaitAnalyzer(age=4) # Assuming age 4 for test
print("Processing video... this might take a moment.")
try:
results = analyzer.process_video(video_path)
# Generate report
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
report_filename = f"gait_analysis_report_{timestamp}.md"
report_path = os.path.join(os.path.dirname(video_path), report_filename)
generate_markdown_report(results, video_path, report_path)
# Helper function to safely format numbers
def fmt(value, decimals=2):
"""Format numeric value or return N/A"""
if value == 'N/A' or value is None:
return 'N/A'
try:
return f"{float(value):.{decimals}f}"
except (ValueError, TypeError):
return 'N/A'
# Extract new observation outputs
summary = results.get("summary", {})
observations = results.get("observations", {})
strategies = results.get("compensatory_strategies", [])
reflex_influence = results.get("reflex_influence", "None observed")
safety_note = results.get("safety_note", "")
weight_dist = results.get("weight_distribution", {})
postural_strength = results.get("postural_strength", {})
clinical_notes = results.get("clinical_notes", [])
print("\n" + "="*60)
print("CLINICAL GAIT ANALYSIS RESULTS")
print("="*60)
# 1. Walking Condition
walking_condition = summary.get("walking_condition", "Not specified")
print(f"\n🚶 WALKING CONDITION: {walking_condition.upper()}")
# 2. Observed Movement Patterns
print(f"\n� OBSERVED MOVEMENT PATTERNS:")
print(f" Trunk: {observations.get('trunk', 'N/A')}")
print(f" Head & Neck: {observations.get('head_neck', 'N/A')}")
print(f" Arms & Hands: {observations.get('arms_hands', 'N/A')}")
print(f" Lower Limbs: {observations.get('lower_limbs', 'N/A')}")
print(f" Symmetry: {observations.get('symmetry', 'N/A')}")
# 3. Compensatory Strategies
print(f"\n💡 COMPENSATORY STRATEGIES:")
if strategies:
for strategy in strategies:
print(f" - {strategy}")
else:
print(" - None identified")
print(f"\n📝 CLINICAL NOTES:")
if clinical_notes:
for note in clinical_notes:
print(f" - {note}")
else:
print(" - None noted")
# 4. Integrated Movement Summary
asymmetry = summary.get("phase_asymmetry_percent", 0)
stability = summary.get("stability_score", 0)
strength = summary.get("strength_score", 0)
weight_shift = summary.get("weight_shift_score", 0)
gait_quality = summary.get("overall_gait_quality", "unknown")
print(f"\n📋 INTEGRATED MOVEMENT SUMMARY:")
print(f" Walking Condition: {walking_condition.upper()}")
print(f" Overall Gait Quality: {gait_quality.upper()}")
print(f" Stability Score: {stability:.0f}/100 | Strength Score: {strength:.0f}/100 | Weight Shift Score: {weight_shift:.0f}/100")
print(f" Movement symmetry shows a {asymmetry:.1f}% phase variance.")
if reflex_influence:
print(f"\n {reflex_influence}")
if safety_note:
print(f"\n ⚠️ {safety_note}")
print("\n" + "="*60)
print("NOTE: This is NOT a medical diagnosis. Consult a healthcare")
print("professional for proper assessment and treatment.")
print("="*60 + "\n")
except Exception as e:
print(f"An error occurred during processing: {e}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
main()
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