Delete test.py

test.py

@@ -1,117 +0,0 @@
-
-import gradio as gr
-import os
-from io import BytesIO
-from PIL import Image, ImageDraw, ImageFont
-from PIL import ImageColor
-import json
-import google.generativeai as genai
-from google.generativeai import types
-from dotenv import load_dotenv
-from IPython.display import display
-
-# 1. SETUP API KEY
-# ----------------
-load_dotenv()
-api_key = os.getenv("Gemini_API_Key") 
-# Configure the Google AI library
-genai.configure(api_key=api_key)
-
-
-# 2. DEFINE MODEL AND INSTRUCTIONS
-
-bounding_box_system_instructions = """
-    Return bounding boxes as a JSON array with labels. Never return masks or code fencing. Limit to 25 objects.
-    If an object is present multiple times, name them according to their unique characteristic (colors, size, position, unique characteristics, etc..).
-      """
-model = genai.GenerativeModel( model_name='gemini-2.5-flash', system_instruction=bounding_box_system_instructions)
-generation_config = genai.types.GenerationConfig(
-        temperature=0.5,
- 
-    )   
-
-
-
-# 3. PREPARE IMAGE AND PROMPT
-
-
-
-
-def parse_json(json_output): 
-    lines = json_output.splitlines()
-    for i, line in enumerate(lines):
-        if line == "```json":
-            json_output = "\n".join(lines[i+1:])  # Remove everything before "```json"
-            json_output = json_output.split("```")[0]  # Remove everything after the closing "```"
-            break
-    return json_output
-print("After parsing JSON from model response...")
-
-  
-def plot_bounding_boxes(im, bounding_boxes):
-    """
-    Plots bounding boxes on an image with labels.
-    """
-    additional_colors = [colorname for (colorname, colorcode) in ImageColor.colormap.items()]
-
-    im = im.copy()
-    width, height = im.size
-    draw = ImageDraw.Draw(im)
-    colors = [
-        'red', 'green', 'blue', 'yellow', 'orange', 'pink', 'purple', 'cyan',
-        'lime', 'magenta', 'violet', 'gold', 'silver'
-    ] + additional_colors
-
-    try:
-        # Use a default font if NotoSansCJK is not available
-        try:
-            font = ImageFont.load_default()
-        except OSError:
-            print("NotoSansCJK-Regular.ttc not found. Using default font.")
-            font = ImageFont.load_default()
-
-        bounding_boxes_json = json.loads(bounding_boxes)
-        for i, bounding_box in enumerate(bounding_boxes_json):
-            color = colors[i % len(colors)]
-            abs_y1 = int(bounding_box["box_2d"][0] / 1000 * height)
-            abs_x1 = int(bounding_box["box_2d"][1] / 1000 * width)
-            abs_y2 = int(bounding_box["box_2d"][2] / 1000 * height)
-            abs_x2 = int(bounding_box["box_2d"][3] / 1000 * width)
-
-            if abs_x1 > abs_x2:
-                abs_x1, abs_x2 = abs_x2, abs_x1
-
-            if abs_y1 > abs_y2:
-                abs_y1, abs_y2 = abs_y2, abs_y1
-
-            # Draw bounding box and label
-            draw.rectangle(((abs_x1, abs_y1), (abs_x2, abs_y2)), outline=color, width=4)
-            if "label" in bounding_box:
-                draw.text((abs_x1 + 8, abs_y1 + 6), bounding_box["label"], fill=color, font=font)
-    except Exception as e:
-        print(f"Error drawing bounding boxes: {e}")
-
-    return im
-
-prompt = "Identify and label the objects in the image. Return only the JSON array of bounding boxes and labels as per the system instructions."
-image = "Images/cookies.jpg"  
-img = Image.open(BytesIO(open(image, "rb").read()))
-print(f"Original image size: {img.size}")
-
-# resize the image to a max width of 1024 while maintaining aspect ratio
-im = Image.open(image).resize((1024, int(1024 * img.size[1] / img.size[0])), Image.Resampling.LANCZOS)
-print(f"Resized image size: {im.size}")
-im.show()
-
-# Run model to find bounding boxes 
-response =  model.generate_content([prompt, im], generation_config=generation_config) 
-print("Raw model response:")
-print(response.text )
-
-bounding_boxes=parse_json(response.text)
-
-
-im_with_boxes = plot_bounding_boxes(im, bounding_boxes)
-display(im_with_boxes)
-im_with_boxes.save("output_imags/cookies_bounding_boxes.jpg")
-print("Bounding boxes plotted on image.")