ai-blocks cv

frontend/core/blocks/apply-gaussian-blur-20241223-163019-869/computations.py → frontend/core/blocks/apply-gaussian-blur-20250115-142408-732/computations.py

@@ -2,13 +2,13 @@
 def compute(image_path, kernel_size):
     '''
     Applies a Gaussian blur to an image using a specified kernel size.
-    
+
     Parameters:
     image_path (str): The file path to the input image that will be blurred.
     kernel_size (int): The size of the kernel to be used for the Gaussian blur. It must be a positive odd integer.
 
     Returns:
-    dict: A dictionary with the file path to the output image that has been blurred.
+    dict: A dictionary with the key 'blurred_image_path' containing the file path to the output image that has been blurred.
     '''
     import cv2
     import os
@@ -30,30 +30,33 @@ def compute(image_path, kernel_size):
 
     return {'blurred_image_path': output_image_path}
 
-
 def generate_fake_image():
     import numpy as np
     import cv2
-    # Create a fake image (e.g., 100x100 with 3 channels for RGB)
-    fake_image = np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8)
-    # Save the fake image to a temporary file
-    path = 'temp_fake_image.jpg'
-    cv2.imwrite(path, fake_image)
-    return path
 
+    # Create a 100x100 pixel image with 3 color channels (R, G, B)
+    fake_image = np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8)
+    fake_image_path = 'fake_image.png'
+    cv2.imwrite(fake_image_path, fake_image)
+    return fake_image_path
 
 def test_compute():
+    # Import necessary modules
     import os
-    # Generate a fake image file path
+
+    # Generate a fake image for testing
     image_path = generate_fake_image()
-    try:
-        # Test the compute function with the generated image and a kernel size
-        result = compute(image_path, 3)
-        print(f"Test passed. Blurred image saved at: {result['blurred_image_path']}")
-    except ValueError as e:
-        print(f"Test failed with error: {e}")
-    # Clean up generated files after the test
+    kernel_size = 3  # An odd integer for the kernel size
+
+    # Call the compute function
+    result = compute(image_path, kernel_size)
+
+    # Check the output
+    blurred_image_path = result['blurred_image_path']
+
+    # Assert if output image exists
+    assert os.path.exists(blurred_image_path), "The blurred image file was not created."
+
+    # Clean up created image files
     os.remove(image_path)
-    generated_blurred_path = 'temp_fake_image_blurred.jpg'
-    if os.path.exists(generated_blurred_path):
-        os.remove(generated_blurred_path)
+    os.remove(blurred_image_path)

frontend/core/blocks/apply-gaussian-blur-20250115-142408-732/requirements.txt

@@ -0,0 +1,2 @@
+numpy==1.26.4
+opencv-python-headless==4.10.0.84

frontend/core/blocks/apply-gaussian-blur-20241223-163019-869/specs.json → frontend/core/blocks/apply-gaussian-blur-20250115-142408-732/specs.json

@@ -2,33 +2,23 @@
     "information": {
         "id": "apply-gaussian-blur",
         "name": "Apply gaussian blur",
-        "description": "Applies a Gaussian blur to an image using a specified kernel size.\n\nParameters:\nimage_path (str): The file path to the input image that will be blurred.\nkernel_size (int): The size of the kernel to be used for the Gaussian blur. It must be a positive odd integer.\n\nReturns:\ndict: A dictionary with the file path to the output image that has been blurred.",
+        "description": "Applies a Gaussian blur to an image using a specified kernel size.\n\nParameters:\nimage_path (str): The file path to the input image that will be blurred.\nkernel_size (int): The size of the kernel to be used for the Gaussian blur. It must be a positive odd integer.\n\nReturns:\ndict: A dictionary with the key 'blurred_image_path' containing the file path to the output image that has been blurred.",
         "system_versions": [
             "0.1"
         ],
         "block_version": "1.0",
-        "block_source": "core/blocks/generated-blocks/apply-gaussian-blur-20241223-163019-869",
+        "block_source": "core/blocks/apply-gaussian-blur-20250115-142408-732",
         "block_type": "compute"
     },
     "inputs": {
         "image_path": {
             "type": "file",
-            "connections": [
-                {
-                    "variable": "path",
-                    "block": "file-af7812m8dijr"
-                }
-            ],
+            "connections": [],
             "relays": []
         },
         "kernel_size": {
             "type": "int",
-            "connections": [
-                {
-                    "variable": "parameter",
-                    "block": "parameter-rk3j8m1elpxq"
-                }
-            ],
+            "connections": [],
             "relays": []
         }
     },

frontend/core/blocks/convert-colored-image-to-grayscale-20241223-163032-427/computations.py → frontend/core/blocks/convert-colored-image-to-grayscale-20250115-142427-862/computations.py

@@ -1,4 +1,3 @@
-
 def compute(image_path):
     '''
     Convert a colored image to a grayscale image.
@@ -27,30 +26,35 @@ def compute(image_path):
 
     return {'grayscale_image_path': grayscale_image_path}
 
-
 def generate_fake_image_path():
-    import numpy as np
     import cv2
+    import numpy as np
     import os
-
-    # Create a fake color image using numpy (e.g., 100x100 pixels with 3 color channels)
-    fake_image = np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8)
-
-    # Define the file path where this fake image will be saved
-    fake_image_path = "fake_image.jpg"
-
-    # Save the generated fake image to the file path
-    cv2.imwrite(fake_image_path, fake_image)
-
-    return fake_image_path
 
+    # Create a fake image
+    fake_image = np.zeros((100, 100, 3), dtype=np.uint8)
+
+    # Define a temporary file path
+    temp_image_path = 'temp_colored_image.jpg'
+
+    # Write the fake image to this path
+    cv2.imwrite(temp_image_path, fake_image)
+
+    return temp_image_path
 
 def test_compute():
-    # Retrieve the generated fake image path
-    image_path = generate_fake_image_path()
-
-    # Run the compute function with the fake image path
-    result = compute(image_path)
-
-    # Print the result to verify that the function ran successfully
+    # Import necessary module
+    import os
+
+    # Generate a fake image path
+    fake_image_path = generate_fake_image_path()
+
+    # Call the function
+    result = compute(fake_image_path)
+
+    # Print the result
     print(result)
+
+    # Remove the temporary images created
+    os.remove(fake_image_path)
+    os.remove(result['grayscale_image_path'])

frontend/core/blocks/convert-colored-image-to-grayscale-20250115-142427-862/requirements.txt

@@ -0,0 +1,2 @@
+numpy==1.26.4
+opencv-python-headless==4.10.0.84

frontend/core/blocks/convert-colored-image-to-grayscale-20241223-163032-427/specs.json → frontend/core/blocks/convert-colored-image-to-grayscale-20250115-142427-862/specs.json

@@ -7,18 +7,13 @@
             "0.1"
         ],
         "block_version": "1.0",
-        "block_source": "core/blocks/generated-blocks/convert-colored-image-to-grayscale-20241223-163032-427",
+        "block_source": "core/blocks/convert-colored-image-to-grayscale-20250115-142427-862",
         "block_type": "compute"
     },
     "inputs": {
         "image_path": {
             "type": "file",
-            "connections": [
-                {
-                    "variable": "path",
-                    "block": "file-af181m72dija"
-                }
-            ],
+            "connections": [],
             "relays": []
         }
     },

frontend/core/blocks/convert-image-to-binary-20241223-163041-154/computations.py → frontend/core/blocks/convert-image-to-binary-20250115-142445-780/computations.py

@@ -1,44 +1,52 @@
+
 def compute(image_path, threshold):
     '''
     Convert a grayscale image to a binary image using a specified threshold.
 
     Parameters:
     image_path (str): The file path to the grayscale image that needs to be converted to binary.
-    threshold (int): The threshold value used to convert the image to binary. Pixel values above this threshold will be set to 255, and those below will be set to 0.
+    threshold (int): The threshold value used to convert the grayscale image to binary. Pixel values greater than or equal to this threshold will be set to white, otherwise black.
 
     Returns:
-    dict: A dictionary with the key 'binary_image_path' and the value as the file path to the resulting binary image after conversion.
+    dict: A dictionary with the key 'binary_image_path' and the value being the file path to the resulting binary image after conversion.
     '''
     import cv2
     import os
 
     # Read the grayscale image
     image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
 
-    # Apply the threshold to convert the image to binary
+    # Check if image is loaded
+    if image is None:
+        raise ValueError('Image not found or unable to load.')
+
+    # Convert the image to binary using the threshold
     _, binary_image = cv2.threshold(image, threshold, 255, cv2.THRESH_BINARY)
-    
-    # Define the output path for the binary image
+
+    # Create the output file path
     base, ext = os.path.splitext(image_path)
     binary_image_path = f"{base}_binary{ext}"
-    
+
     # Save the binary image
     cv2.imwrite(binary_image_path, binary_image)
-    
+
     return {'binary_image_path': binary_image_path}
 
 def generate_fake_image():
     import numpy as np
     import cv2
-
-    # Create a fake grayscale image using a numpy array
-    fake_image = np.random.randint(0, 256, (100, 100), dtype=np.uint8)
+
+    # Create a 10x10 grayscale image with random values
+    fake_image = np.random.randint(0, 256, (10, 10), dtype=np.uint8)
+
+    # Save it to a temporary location
     fake_image_path = 'fake_image.png'
     cv2.imwrite(fake_image_path, fake_image)
     return fake_image_path
 
+
 def test_compute():
     image_path = generate_fake_image()
     threshold = 128
-    output = compute(image_path, threshold)
-    print(output)
+    result = compute(image_path, threshold)
+    print(result)  # To verify the output

frontend/core/blocks/convert-image-to-binary-20250115-142445-780/requirements.txt

@@ -0,0 +1,2 @@
+numpy==1.26.4
+opencv-python-headless==4.10.0.84

frontend/core/blocks/convert-image-to-binary-20241223-163041-154/specs.json → frontend/core/blocks/convert-image-to-binary-20250115-142445-780/specs.json

@@ -2,33 +2,23 @@
     "information": {
         "id": "convert-image-to-binary",
         "name": "Convert image to binary",
-        "description": "Convert a grayscale image to a binary image using a specified threshold.\n\nParameters:\nimage_path (str): The file path to the grayscale image that needs to be converted to binary.\nthreshold (int): The threshold value used to convert the image to binary. Pixel values above this threshold will be set to 255, and those below will be set to 0.\n\nReturns:\ndict: A dictionary with the key 'binary_image_path' and the value as the file path to the resulting binary image after conversion.",
+        "description": "Convert a grayscale image to a binary image using a specified threshold.\n\nParameters:\nimage_path (str): The file path to the grayscale image that needs to be converted to binary.\nthreshold (int): The threshold value used to convert the grayscale image to binary. Pixel values greater than or equal to this threshold will be set to white, otherwise black.\n\nReturns:\ndict: A dictionary with the key 'binary_image_path' and the value being the file path to the resulting binary image after conversion.",
         "system_versions": [
             "0.1"
         ],
         "block_version": "1.0",
-        "block_source": "core/blocks/generated-blocks/convert-image-to-binary-20241223-163041-154",
+        "block_source": "core/blocks/convert-image-to-binary-20250115-142445-780",
         "block_type": "compute"
     },
     "inputs": {
         "image_path": {
             "type": "file",
-            "connections": [
-                {
-                    "variable": "path",
-                    "block": "file-af181m72dija"
-                }
-            ],
+            "connections": [],
             "relays": []
         },
         "threshold": {
             "type": "int",
-            "connections": [
-                {
-                    "variable": "parameter",
-                    "block": "parameter-adzakalp9mlc"
-                }
-            ],
+            "connections": [],
             "relays": []
         }
     },